P.Mean: Interesting articles, books, quotes, or websites added to this site for 2009 (created 2009-01-21)

P.Mean: Interesting articles, books, quotes, or websites added to this site for 2009 (created 2009-01-21).

Please also consult the page for other years:

2010, and

2008.

December

Jonathan J. Deeks. Issues in the selection of a summary statistic for meta-analysis of clinical trials with binary outcomes. Statistics in Medicine. 2002;21(11):1575-1600. Abstract: "Meta-analysis of binary data involves the computation of a weighted average of summary statistics calculated for each trial. The selection of the appropriate summary statistic is a subject of debate due to conflicts in the relative importance of mathematical properties and the ability to intuitively interpret results. This paper explores the process of identifying a summary statistic most likely to be consistent across trials when there is variation in control group event rates. Four summary statistics are considered: odds ratios (OR); risk differences (RD) and risk ratios of beneficial (RR(B)); and harmful outcomes (RR(H)). Each summary statistic corresponds to a different pattern of predicted absolute benefit of treatment with variation in baseline risk, the greatest difference in patterns of prediction being between RR(B) and RR(H). Selection of a summary statistic solely based on identification of the best-fitting model by comparing tests of heterogeneity is problematic, principally due to low numbers of trials. It is proposed that choice of a summary statistic should be guided by both empirical evidence and clinically informed debate as to which model is likely to be closest to the expected pattern of treatment benefit across baseline risks. Empirical investigations comparing the four summary statistics on a sample of 551 systematic reviews provide evidence that the RR and OR models are on average more consistent than RD, there being no difference on average between RR and OR. From a second sample of 114 meta-analyses evidence indicates that for interventions aimed at preventing an undesirable event, greatest absolute benefits are observed in trials with the highest baseline event rates, corresponding to the model of constant RR(H). The appropriate selection for a particular meta-analysis may depend on understanding reasons for variation in control group event rates; in some situations uncertainty about the choice of summary statistic will remain. Copyright © 2002 John Wiley & Sons, Ltd." [Accessed December 18, 2009]. Available at: http://dx.doi.org/10.1002/sim.1188.
Thomas B Newman. The power of stories over statistics. BMJ. 2003;327(7429):1424-1427. Excerpt: "Neonatal jaundice and infant safety on aeroplanes provide two lessons on the power of narrative, rather than statistical evidence, in determining practice." [Accessed December 10, 2009]. Available at: http://www.bmj.com.
Raj Bhopal. Seven mistakes and potential solutions in epidemiology, including a call for a World Council of Epidemiology and Causality. Emerging Themes in Epidemiology. 2009;6(1):6. Abstract: "All sciences make mistakes, and epidemiology is no exception. I have chosen 7 illustrative mistakes and derived 7 solutions to avoid them. The mistakes (Roman numerals denoting solutions) are: 1. Failing to provide the context and definitions of study populations. (I Describe the study population in detail.). 2. Insufficient attention to evaluation of error. (II Don't pretend error does not exist.). 3. Not demonstrating comparisons are like-for-like. (III Start with detailed comparisons of groups.). 4. Either overstatement or understatement of the case for causality. (IV Never say this design cannot contribute to causality or imply causality is ensured by your design.). 5. Not providing both absolute and relative summary measures. (V Give numbers, rates and comparative measures, and adjust summary measures such as odds ratios appropriately.). 6. In intervention studies not demonstrating general health benefits. (VI Ensure general benefits (mortality/morbidity) before recommending application of cause-specific findings.). 7. Failure to utilise study data to benefit populations. (VII Establish a World Council on Epidemiology to help infer causality from associations and apply the work internationally.). Analysis of these and other common mistakes is needed to benefit from the increasing discovery of associations that will be multiplying as data mining, linkage, and large-scale scale epidemiology become commonplace." [Accessed December 10, 2009]. Available at: http://www.ete-online.com/content/6/1/6.
Nathaniel D. Mercaldo, Kit F. Lau, Xiao H. Zhou. Confidence intervals for predictive values with an emphasis to case-control studies. Statistics in Medicine. 2007;26(10):2170-2183. Abstract: "The accuracy of a binary-scale diagnostic test can be represented by sensitivity (Se), specificity (Sp) and positive and negative predictive values (PPV and NPV). Although Se and Sp measure the intrinsic accuracy of a diagnostic test that does not depend on the prevalence rate, they do not provide information on the diagnostic accuracy of a particular patient. To obtain this information we need to use PPV and NPV. Since PPV and NPV are functions of both the accuracy of the test and the prevalence of the disease, constructing their confidence intervals for a particular patient is not straightforward. In this paper, a novel method for the estimation of PPV and NPV, as well as their confidence intervals, is developed. For both predictive values, standard, adjusted and their logit transformed-based confidence intervals are compared using coverage probabilities and interval lengths in a simulation study. These methods are then applied to two case-control studies: a diagnostic test assessing the ability of the e4 allele of the apolipoprotein E gene (ApoE.e4) on distinguishing patients with late-onset Alzheimer's disease (AD) and a prognostic test assessing the predictive ability of a 70-gene signature on breast cancer metastasis. Copyright © 2006 John Wiley & Sons, Ltd." [Accessed December 10, 2009]. Available at: http://dx.doi.org/10.1002/sim.2677.
Byron Wallace, Christopher Schmid, Joseph Lau, Thomas Trikalinos. Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data. BMC Medical Research Methodology. 2009;9(1):80. Abstract: "BACKGROUND: Meta-analysis is increasingly used as a key source of evidence synthesis to inform clinical practice. The theory and statistical foundations of meta-analysis continually evolve, providing solutions to many new and challenging problems. In practice, most meta-analyses are performed in general statistical packages or dedicated meta-analysis programs. RESULTS: Herein, we introduce Meta-Analyst, a novel, powerful, intuitive, and free meta-analysis program for the meta-analysis of a variety of problems. Meta-Analyst is implemented in C# atop of the Microsoft .NET framework, and features a graphical user interface. The software performs several meta-analysis and meta-regression models for binary and continuous outcomes, as well as analyses for diagnostic and prognostic test studies in the frequentist and Bayesian frameworks. Moreover, Meta-Analyst includes a flexible tool to edit and customize generated meta-analysis graphs (e.g., forest plots) and provides output in many formats (images, Adobe PDF, Microsoft Word-ready RTF). The software architecture employed allows for rapid changes to be made to either the Graphical User Interface (GUI) or to the analytic modules. We verified the numerical precision of Meta-Analyst by comparing its output with that from standard meta-analysis routines in Stata over a large database of 11,803 meta-analyses of binary outcome data, and 6,881 meta-analyses of continuous outcome data from the Cochrane Library of Systematic Reviews. Results from analyses of diagnostic and prognostic test studies have been verified in a limited number of meta-analyses versus MetaDisc and MetaTest. Bayesian statistical analyses use the OpenBUGS calculation engine (and are thus as accurate as the standalone OpenBUGS software). CONCLUSION: We have developed and validated a new program for conducting meta-analyses that combines the advantages of existing software for this task." [Accessed December 9, 2009]. Available at: http://www.biomedcentral.com/1471-2288/9/80.
Miguel Roig. Avoiding plagiarism, self-plagiarism, and other questionable writing practices: A guide to ethical writing. Excerpt: "In recognizing the importance of educating aspiring scientists in the responsible conduct of research (RCR), the Office of Research Integrity (ORI), began sponsoring in 2002 the creation of instructional resources to address this pressing need. The present guide on avoiding plagiarism and other inappropriate writing practices was created, in part, to meet this need. Its purpose is to help students, as well as professionals, identify and prevent such practices and to develop an awareness of ethical writing. This guide is one of the many products stemming from ORI’s educational initiatives in the RCR." [Accessed December 7, 2009]. Available at: http://facpub.stjohns.edu/~roigm/plagiarism/Index.html.
PSCA International. Privacy needed for patients' data. Excerpt: "Approximately one half of patients and the general public believe that identifiable patient data should never be used for research without consent. Whilst only 11 per cent of researchers believed this should never happen, 53 per cent of the general public and 46 per cent of patients thought it was unacceptable without prior consent. But more than half of researchers thought patient identifiable data should be used without patient consent if it had first been reviewed by the Patient Information Advisory Group (PIAG). Only 30 per cent of both patients and the general public agreed." [Accessed December 5, 2009]. Available at: http://www.publicservice.co.uk/news_story.asp?id=11486.
Trisha Greenhalgh. Narrative based medicine: Narrative based medicine in an evidence based world. BMJ. 1999;318(7179):323-325. Excerpt: "In a widely quoted riposte to critics who accused them of naive empiricism, Sackett and colleagues claimed that "the practice of evidence based medicine means integrating individual clinical expertise with the best available external clinical evidence .... By individual clinical expertise we mean the proficiency and judgment that individual clinicians acquire through clinical experience and clinical practice." Sackett and colleagues were anxious to acknowledge that there is an art to medicine as well as an objective empirical science but they did not attempt to define or categorise the elusive quality of clinical competence. This article explores the dissonance between the "science" of objective measurement and the "art" of clinical proficiency and judgment, and attempts to integrate these different perspectives on clinical method." [Accessed December 5, 2009]. Available at: http://www.bmj.com/cgi/content/full/318/7179/323.
Vera Kalitzkus, Peter F. Matthiessen. Narrative-Based Medicine: Potential, Pitfalls, and Practice. The Permanente Journal. 13(1):80-86. Excerpt: "Narratives have always been a vital part of medicine. Stories about patients, the experience of caring for them, and their recovery from illness have always been shared—among physicians as well as among patients and their relatives. With the evolution of “modern” medicine, narratives were increasingly neglected in favor of “facts and findings,” which were regarded as more scientific and objective. Now, in recent years medical narrative is changing—from the stories about patients and their illnesses, patient narratives and the unfolding and interwoven story between health care professionals and patients are both gaining momentum, leading to the creation or defining of narrative-based medicine (NBM). The term was coined deliberately to mark its distinction from evidence-based medicine (EBM); in fact, NBM was propagated to counteract the shortcomings of EBM.1,2 But what is NBM? Is it a specific therapeutic tool, a special form of physician-patient communication, a qualitative research tool, or does it simply signify a particular attitude towards patients and doctoring? It can be all of the above with different forms or genres of narrative or practical approach called for depending on the field of application. In this article we will give a systematic overview of NBM: a short historic background; the various narrative genres; and an analysis of how the genres can be effectively applied in theory, research, and practice in the medical field, with a focus on possibilities and limitations of a narrative approach. " [Accessed December 5, 2009]. Available at: http://xnet.kp.org/permanentejournal/winter09/narrativemedicine.html.
David C. Howell. Resampling Statistics: Randomization and the Bootstrap. Excerpt: "This set of pages is intended to serve two purposes. On the one hand, it was written to accompany a set of Windows© programs that I have written. The main program is named Resampling.exe, and is available on disk and can be downloaded from www.uvm.edu/~dhowell/StatPages/Resampling/ResamplingPackage .zip. The second purpose of these pages is to elaborate on resampling techniques and the theory behind them. " [Accessed December 5, 2009]. Available at: http://www.uvm.edu/~dhowell/StatPages/Resampling/Resampling.html.
Julian L. Simon. Resampling: The New Statistics. Excerpt: "This text grew out of chapters in the 1969 edition of Basic Research Methods in Social Science by the same author, and contains the first published example of what was later called the bootstrap. Simon is best known for his research in demography, population and the economics of natural resources, and gained fame when the noted biologist Paul Ehrlich selected five commodities and bet Simon that scarcity would drive their prices up over the period of the bet (in fact, their prices all dropped). Resampling: The New Statistics contains a number of examples in Resampling Stats, a computer program originated by Simon, but can be read on its own without the program." [Accessed December 5, 2009]. Available at: http://www.resample.com/content/text/index.shtml.

November
Mei-Wei Chang, Roger Brown, Susan Nitzke. Participant recruitment and retention in a pilot program to prevent weight gain in low-income overweight and obese mothers. BMC Public Health. 2009;9(1):424. Abstract: Background Recruitment and retention are key functions for programs promoting nutrition and other lifestyle behavioral changes in low-income populations. This paper describes strategies for recruitment and retention and presents predictors of early (two-month post intervention) and late (eight-month post intervention) dropout (non retention) and overall retention among young, low-income overweight and obese mothers participating in a community-based randomized pilot trial called Mothers In Motion. Methods Low-income overweight and obese African American and white mothers ages 18 to 34 were recruited from the Special Supplemental Nutrition Program for Women, Infants, and Children in southern Michigan. Participants (n = 129) were randomly assigned to an intervention (n = 64) or control (n = 65) group according to a stratification procedure to equalize representation in two racial groups (African American and white) and three body mass index categories (25.0-29.9 kg/m2, 30.0-34.9 kg/m2, and 35.0-39.9 kg/m2). The 10-week theory-based culturally sensitive intervention focused on healthy eating, physical activity, and stress management messages that were delivered via an interactive DVD and reinforced by five peer-support group teleconferences. Forward stepwise multiple logistic regression was performed to examine whether dietary fat, fruit and vegetable intake behaviors, physical activity, perceived stress, positive and negative affect, depression, and race predicted dropout as data were collected two- month and eight-month after the active intervention phase. Results Trained personnel were successful in recruiting subjects. Increased level of depression was a predictor of early dropout (odds ratio = 1.04; 95% CI = 1.00, 1.08; p = 0.03). Greater stress predicted late dropout (odds ratio = 0.20; 95% CI = 0.00, 0.37; p = 0.01). Dietary fat, fruit, and vegetable intake behaviors, physical activity, positive and negative affect, and race were not associated with either early or late dropout. Less negative affect was a marginal predictor of participant retention (odds ratio = 0.57; 95% CI = 0.31, 1.03; p = 0.06). CONCLUSIONS:Dropout rates in this study were higher for participants who reported higher levels of depression and stress. Trial registration: Current Controlled Trials NCT00944060 [Accessed November 30, 2009]. Available at: http://www.biomedcentral.com/1471-2458/9/424.
Cora Craig, Christine Cameron, Joe Griffiths, et al. Non-response bias in physical activity trend estimates. BMC Public Health. 2009;9(1):425. Abstract: BACKGROUND: Increases in reported leisure time physical activity (PA) and obesity have been observed in several countries. One hypothesis for these apparently contradictory trends is differential bias in estimates over time. The purpose of this short report is to examine the potential impact of changes in response rates over time on the prevalence of adequate PA in Canadian adults. METHODS:Participants were recruited in representative national telephone surveys of PA from 1995-2007. Differences in PA prevalence estimates between participants and those hard to reach were assessed using Student's t tests adjusted for multiple comparisons. RESULTS:The number of telephone calls required to reach and speak with someone in the household increased over time, as did the percentage of selected participants who initially refused during the first interview attempt. A higher prevalence of adequate PA was observed with 5-9 attempts to reach anyone in the household in 1999-2002, but this was not significant after adjustment for multiple comparisons. CONCLUSIONS:No significant impact on PA trend estimates was observed due to differential non response rates. It is important for health policy makers to understand potential biases and how these may affect secular trends in all aspects of the energy balance equation. [Accessed November 29, 2009]. Available at: http://www.biomedcentral.com/1471-2458/9/425.
Tracey Sach, David Whynes. Men and women: beliefs about cancer and about screening. BMC Public Health. 2009;9(1):431. Abstract: BACKGROUND:Cancer screening programmes in England are publicly-funded. Professionals' beliefs in the public health benefits of screening can conflict with individuals' entitlements to exercise informed judgement over whether or not to participate. The recognition of the importance of individual autonomy in decision making requires greater understanding of the knowledge, attitudes and beliefs upon which people's screening choices are founded. Until recently, the technology available required that cancer screening be confined to women. This study aimed to discover whether male and female perceptions of cancer and of screening differ.METHODS:Data on the public's cancer beliefs were collected by means of a postal survey (anonymous questionnaire). Two general practices based in Nottingham and in Mansfield, in east-central England, sent questionnaires to registered patients aged 30 to 70 years. 1,808 completed questionnaires were returned for analysis, 56.5 per cent from women. RESULTS:Women were less likely to underestimate overall cancer incidence, although each sex was more likely to cite a sex-specific cancer as being amongst the most common cancer site. In terms of risk factors, men were most uncertain about the role of stress and sexually-transmitted diseases, whereas women were more likely to rate excessive alcohol and family history as major risk factors. The majority of respondents believed the public health care system should provide cancer screening, but significantly more women than men reported having benefiting from the nationally-provided screening services. Those who were older, in better health or had longer periods of formal education were less worried about cancer than those who had illness experiences, lower incomes, or who were smokers. Actual or potential participation in bowel screening was higher amongst those who believed bowel cancer to be common and amongst men, despite women having more substantial worries about cancer than men. CONCLUSIONS:Our results suggest that men's and women's differential knowledge of cancer correlates with women's closer involvement with screening. Even so, men were neither less positive about screening nor less likely to express a willingness to participate in relevant screening in the future. It is important to understand gender-related differences in knowledge and perceptions of cancer, if health promotion resources are to be allocated efficiently. [Accessed November 30, 2009]. Available at: http://www.biomedcentral.com/1471-2458/9/431.
Kerrie Sanders, Amanda Stuart, Elizabeth Merriman, et al. Trials and tribulations of recruiting 2,000 older women onto a clinical trial investigating falls and fractures: Vital D study. BMC Medical Research Methodology. 2009;9(1):78. Abstract: BACKGROUND: Randomised, placebo-controlled trials are needed to provide evidence demonstrating safe, effective interventions that reduce falls and fractures in the elderly. The quality of a clinical trial is dependent on successful recruitment of the target participant group. This paper documents the successes and failures of recruiting over 2,000 women aged at least 70 years and at higher risk of falls or fractures onto a placebo-controlled trial of six years duration. The characteristics of study participants at baseline are also described for this study.METHODS:The Vital D Study recruited older women identified at high risk of fracture through the use of an eligibility algorithm, adapted from identified risk factors for hip fracture. Participants were randomised to orally receive either 500,000 IU vitamin D3 (cholecalciferol) or placebo every autumn for three to five consecutive years. A variety of recruitment strategies were employed to attract potential participants. RESULTS:Of the 2,317 participants randomised onto the study, 74% (n= 1716/ 2317) were consented onto the study in the last five months of recruiting. This was largely due to the success of a targeted mail-out. Prior to this only 541 women were consented in the 18 months of recruiting. A total of 70% of all participants were recruited as a result of targeted mail-out. The response rate from the letters increased from 2 to 7% following revision of the material by a public relations company. Participant demographic or risk factor profile did not differ between those recruited by targeted mail-outs compared with other methods.CONCLUSIONS:The most successful recruitment strategy was the targeted mail-out and the response rate was no higher in the local region where the study had extensive exposure through other recruiting strategies. The strategies that were labour-intensive and did not result in successful recruitment include the activities directed towards the GP medical centres. Comprehensive recruitment programs employ overlapping strategies simultaneously with ongoing assessment of recruitment rates. In our experience, and others direct mail-outs work best although rights to privacy must be respected. Trial registration: ISRCTN83409867 and ACTR12605000658617. [Accessed November 30, 2009]. Available at: http://www.biomedcentral.com/1471-2288/9/78.
Fujian Song, Sheetal Parekh-Bhurke, Lee Hooper, et al. Extent of publication bias in different categories of research cohorts: a meta-analysis of empirical studies. BMC Medical Research Methodology. 2009;9(1):79.Abstract: BACKGROUND:The validity of research synthesis is threatened if published studies comprise a biased selection of all studies that have been conducted. We conducted a meta-analysis to ascertain the strength and consistency of the association between study results and formal publication. METHODS:The Cochrane Methodology Register Database, MEDLINE and other electronic bibliographic databases were searched (to May 2009) to identify empirical studies that tracked a cohort of studies and reported the odds of formal publication by study results. Reference lists of retrieved articles were also examined for relevant studies. Odds ratios were used to measure the association between formal publication and significant or positive results. Included studies were separated into subgroups according to starting time of follow-up, and results from individual cohort studies within the subgroups were quantitatively pooled. RESULTS:We identified 12 cohort studies that followed up research from inception, four that included trials submitted to a regulatory authority, 28 that assessed the fate of studies presented as conference abstracts, and four cohort studies that followed manuscripts submitted to journals. The pooled odds ratio of publication of studies with positive results, compared to those without positive results (publication bias) was 2.78 (95% CI: 2.10 to 3.69) in cohorts that followed from inception, 5.00 (95% CI: 2.01 to 12.45) in trials submitted to regulatory authority, 1.70 (95% CI: 1.44 to 2.02) in abstract cohorts, and 1.06 (95% CI: 0.80 to 1.39) in cohorts of manuscripts. CONCLUSIONS:Dissemination of research findings is likely to be a biased process. Publication bias appears to occur early, mainly before the presentation of findings at conferences or submission of manuscripts to journals. [Accessed November 29, 2009]. Available at: http://www.biomedcentral.com/1471-2288/9/79.
Jon Cohen. Mission Improbable: A Concise and Precise Definition of P-Value. ScienceNOW Daily News, October 30, 2009. Excerpt: Victor De Gruttola, the chair of biostatistics at the Harvard School of Public Health, is passionate about his p-values. That's why he was apoplectic last month when an esteemed colleague and prominent AIDS vaccine researcher spoke with him about the widely publicized results of the largest ever AIDS vaccine trial. "The probability that this vaccine didn't work was only 4%," said his colleague, whom we will call Thor to spare from further embarrassment. [Accessed November 18, 2009]. Available at: http://sciencenow.sciencemag.org/cgi/content/full/2009/1030/1
Wynn L, Paul H. Mason, and Kristina Everett. Social Sciences Ethics Training - Macquarie University. Excerpt: Welcome to Macquarie University's Online Ethics Training Module! This free educational resource examines the particular ethical issues raised by social science and humanities research. The training module is divided into 6 basic parts. You can start and stop reading at any point in the module, and you can close it and return to it later. After you have reviewed the entire module, there is a quiz that tests your comprehension of the material. [Accessed November 17, 2009]. Available at: http://www.mq.edu.au/ethics_training/
Carley S, Dosman S, Jones SR, Harrison M. Simple nomograms to calculate sample size in diagnostic studies. Emerg Med J. 2005;22(3):180-181. Abstract: Objectives: To produce an easily understood and accessible tool for use by researchers in diagnostic studies. Diagnostic studies should have sample size calculations performed, but in practice, they are performed infrequently. This may be due to a reluctance on the part of researchers to use mathematical formulae. Methods: Using a spreadsheet, we derived nomograms for calculating the number of patients required to determine the precision of a test’s sensitivity or specificity. Results: The nomograms could be easily used to determine the sensitivity and specificity of a test. Conclusions: In addition to being easy to use, the nomogram allows deduction of a missing parameter (number of patients, confidence intervals, prevalence, or sensitivity/specificity) if the other three are known. The nomogram can also be used retrospectively by the reader of published research as a rough estimating tool for sample size calculations. [Accessed November 16, 2009]. Available at: http://emj.bmj.com/cgi/content/abstract/22/3/180
Baron J. R site search. Excerpt: This search will allow you to search the contents of the R functions, package vignettes, task views, and R-help mail archives. [Accessed November 13, 2009]. Available at: http://search.r-project.org/nmz.html
Pearl DK. Consortium for the Advancement of Undergraduate Statistics Education (CAUSE). Excerpt: Arising from a strategic initiative of the American Statistical Association, CAUSE is a national organization whose mission is to support and advance undergraduate statistics education, in four target areas: resources, professional development, outreach, and research. The overarching goals in each area are: * Resources: Collect, review, develop, and disseminate resources for members of the undergraduate statistics education community. * Professional Development: Coordinate, develop, and disseminate opportunities, programs, and workshops for teachers and others involved in statistics education projects and initiatives, present and future. * Outreach: Establish and promote communication and collaborations among statistics educators, as well as with other professional organizations and disciplines that are concerned with undergraduate statistics education. * Research: Establish the area of statistics education research as a recognized discipline with a visible presence. Prepare and connect researchers from all disciplines that conduct research in statistics education. Our primary vehicle for communication is CAUSEweb.org, which is supported by a grant from the National Science Foundation. [Accessed November 11, 2009]. Available at: http://www.causeweb.org/
Hamza T, Arends L, van Houwelingen H, Stijnen T. Multivariate random effects meta-analysis of diagnostic tests with multiple thresholds. BMC Medical Research Methodology. 2009;9(1):73. Abstract: Bivariate random effects meta-analysis of diagnostic tests is becoming a well established approach when studies present one two-by-two table or one pair of sensitivity and specificity. When studies present multiple thresholds for test positivity, usually meta-analysts reduce the data to a two-by-two table or take one threshold value at a time and apply the well developed meta-analytic approaches. However, this approach does not fully exploit the data. In this paper we generalize the bivariate random effects approach to the situation where test results are presented with k thresholds for test positivity, resulting in a 2 by (k+1) table per study. The model can be fitted with standard likelihood procedures in statistical packages such as SAS (Proc NLMIXED). We follow a multivariate random effects approach; i.e., we assume that each study estimates a study specific ROC curve that can be viewed as randomly sampled from the population of all ROC curves of such studies. In contrast to the bivariate case, where nothing can be said about the shape of study specific ROC curves without additional untestable assumptions, the multivariate model can be used to describe study specific ROC curves. The models are easily extended with study level covariates. Results The method is illustrated using published meta-analysis data. The SAS NLMIXED syntax is given in the appendix. We conclude that the multivariate random effects meta-analysis approach is an appropriate and convenient framework to meta-analyse studies with multiple threshold without losing any information by dichotomizing the test results. [Accessed November 11, 2009]. Available at: http://www.biomedcentral.com/1471-2288/9/73
Verlen J. Product Naming Guide. Description: In a move that is quite surprising to me, SPSS decided to rename all of its products. The basic SPSS program is now called PASW Statistics. PASW is an acronym for Predictive Analytics Software. This letter from the Vice President R&D and Chief Product Strategist of SPSS Inc. explains why the names were changed and offers a guide between old and new names of products of SPSS, Inc. [Accessed November 11, 2009]. Available at: http://www.spss.com/software/product-name-guide/

October
Greenhalgh T, Peacock R. Effectiveness and efficiency of search methods in systematic reviews of complex evidence: audit of primary sources. BMJ. 2005;331(7524):1064-1065. Excerpt: In systematic reviews of complex and heterogeneous evidence (such as those undertaken for management and policymaking questions) formal protocol-driven search strategies may fail to identify important evidence. Informal approaches such as browsing, "asking around," and being alert to serendipitous discovery can substantially increase the yield and efficiency of search efforts. "Snowball" methods such as pursuing references of references and electronic citation tracking are especially powerful for identifying high quality sources in obscure locations. [Accessed October 29, 2009] Available at: http://www.bmj.com/cgi/content/abstract/331/7524/1064.
Sherman K, Hawkes R, Ichikawa L, et al. Comparing recruitment strategies in a study of acupuncture for chronic back pain. BMC Medical Research Methodology. 2009;9(1):69. Abstract: Background Meeting recruitment goals is challenging for many clinical trials conducted in primary care populations. Little is known about how the use of different recruitment strategies affects the types of individuals choosing to participate or the conclusions of the study. Methods A secondary analysis was performed using data from participants recruited to a clinical trial evaluating acupuncture for chronic back pain among primary care patients in a large integrated health care organization. We used two recruitment methods: mailed letters of invitation and an advertisement in the health plan's magazine. For these two recruitment methods, we compared recruitment success (% randomized, treatment completers, drop outs and losses to follow-up), participant characteristics, and primary clinical outcomes. A linear regression model was used to test for interaction between treatment group and recruitment method. Results Participants recruited via mailed letters closely resembled those responding to the advertisement in terms of demographic characteristics, most aspects of their back pain history and current episode and beliefs and expectations about acupuncture. No interaction between method of recruitment and treatment group was seen, suggesting that study outcomes were not affected by recruitment strategy. Conclusion In this trial, the two recruitment strategies yielded similar estimates of treatment effectiveness. However, because this finding may not apply to other recruitment strategies or trial circumstances, trials employing multiple recruitment strategies should evaluate the effect of recruitment strategy on outcome. Trial registration: Clinical Trials.gov NCT 00065585. [Accessed October 28, 2009]. Available at: http://www.biomedcentral.com/1471-2288/9/69
University of Georgia. Archives of SPSSX-L@LISTSERV.UGA.EDU. Description: This site allows you to join the email discussion group about SPSS or to review its archives. Available at: http://www.listserv.uga.edu/archives/spssx-l.html [Accessed October 15, 2009].
Garfield J. Assessment Resource Tools for Improving Statistical Thinking. Excerpt: Our goal is to help teachers assess statistical literacy, statistical reasoning, and statistical thinking in first courses of statistics. This Web site provides a variety of assessment resources for teaching first courses in Statistics. Available at: https://app.gen.umn.edu/artist/index.html [Accessed October 15, 2009].
U.S. Food and Drug Administration. Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials. Excerpt: This document provides guidance on statistical aspects of the design and analysis of clinical trials for medical devices that use Bayesian statistical methods. The purpose of this guidance is to discuss important statistical issues in Bayesian clinical trials for medical devices and not to describe the content of a medical device submission. Further, while this document provides guidance on many of the statistical issues that arise in Bayesian clinical trials, it is not intended to be all-inclusive. The statistical literature is rich with books and papers on Bayesian theory and methods; a selected bibliography has been included for further discussion of specific topics. FDA’s guidance documents, including this guidance, do not establish legally enforceable responsibilities. Instead, guidances describe the Agency’s current thinking on a topic and should be viewed only as recommendations, unless specific regulatory or statutory requirements are cited. The use of the word should in Agency guidances means that something is suggested or recommended, but not required. Available at: www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/GuidanceDocuments/ucm071072.htm [Accessed October 13, 2009].
du Prie M. Standards for Research in Child Health. Description: This website is an effort to develop guidleines for pediatric research that is evidence-based where possible and a consensus among experts where there is no evidence. Available at: http://www.starchildhealth.org/ [Accessed October 11, 2009].
McKay J, Bradley N, Lough M, Bowie P. A review of significant events analysed in general practice: implications for the quality and safety of patient care. BMC Family Practice. 2009;10(1):61. Abstract: BACKGROUND: Significant event analysis (SEA) is promoted as a team-based approach to enhancing patient safety through reflective learning. Evidence of SEA participation is required for appraisal and contractual purposes in UK general practice. A voluntary educational model in the west of Scotland enables general practitioners (GPs) and doctors-in-training to submit SEA reports for feedback from trained peers. We reviewed reports to identify the range of safety issues analysed, learning needs raised and actions taken by GP teams. METHOD: Content analysis of SEA reports submitted in an 18 month period between 2005 and 2007. RESULTS: 191 SEA reports were reviewed. 48 described patient harm (25.1%). A further 109 reports (57.1%) outlined circumstances that had the potential to cause patient harm. Individual 'error' was cited as the most common reason for event occurrence (32.5%). Learning opportunities were identified in 182 reports (95.3%) but were often non-specific professional issues not shared with the wider practice team. 154 SEA reports (80.1%) described actions taken to improve practice systems or professional behaviour. However, non-medical staff were less likely to be involved in the changes resulting from event analyses describing patient harm (p < 0.05) CONCLUSION: The study provides some evidence of the potential of SEA to improve healthcare quality and safety. If applied rigorously, GP teams and doctors in training can use the technique to investigate and learn from a wide variety of quality issues including those resulting in patient harm. This leads to reported change but it is unclear if such improvement is sustained. Available at: http://www.biomedcentral.com/1471-2296/10/61 [Accessed October 11, 2009].
Klotsche J, Ferger D, Pieper L, Rehm J, Wittchen H. A novel nonparametric approach for estimating cut-offs in continuous risk indicators with application to diabetes epidemiology. BMC Medical Research Methodology. 2009;9(1):63. Abstract: BACKGROUND: Epidemiological and clinical studies, often including anthropometric measures, have established obesity as a major risk factor for the development of type 2 diabetes. Appropriate cut-off values for anthropometric parameters are necessary for prediction or decision purposes. The cut-off corresponding to the Youden-Index is often applied in epidemiology and biomedical literature for dichotomizing a continuous risk indicator. METHODS: Using data from a representative large multistage longitudinal epidemiological study in a primary care setting in Germany, this paper explores a novel approach for estimating optimal cut-offs of anthropomorphic parameters for predicting type 2 diabetes based on a discontinuity of a regression function in a nonparametric regression framework. RESULTS: The resulting cut-off corresponded to values obtained by the Youden Index (maximum of the sum of sensitivity and specificity, minus one), often considered the optimal cut-off in epidemiological and biomedical research. The nonparametric regression based estimator was compared to results obtained by the established methods of the Receiver Operating Characteristic plot in various simulation scenarios and based on bias and root mean square error, yielded excellent finite sample properties. CONCLUSION: It is thus recommended that this nonparametric regression approach be considered as valuable alternative when a continuous indicator has to be dichotomized at the Youden Index for prediction or decision purposes. Available at: http://www.biomedcentral.com/1471-2288/9/63 [Accessed October 11, 2009].

September
Dyas J, Apeky T, Tilling M, Siriwardena A. Strategies for improving patient recruitment to focus groups in primary care: a case study reflective paper using an analytical framework. BMC Medical Research Methodology. 2009;9(1):65. Excerpt: Recruitment to focus group studies should be considered in two distinct phases; getting potential participants to contact the researcher, and converting those contacts into attendance. The difficulty of recruitment in primary care is underemphasised in the literature especially where people do not regularly come together, typified by this case study of patients with sleep problems. We recommend training GPs and nurses to recruit patients during consultations. Multiple recruitment methods should be employed from the outset and the need to build topic related non-financial incentives into the group meeting should be considered. Recruitment should be monitored regularly with barriers addressed iteratively as a study progresses. Available at: http://www.biomedcentral.com/1471-2288/9/65 [Accessed September 29, 2009].
McCandless L, Gustafson P, Austin P, Levy A. Covariate balance in a Bayesian propensity score analysis of beta blocker therapy in heart failure patients. Epidemiologic Perspectives & Innovations. 2009;6(1):5. Available at: http://www.epi-perspectives.com/content/6/1/5 [Accessed September 14, 2009]. Abstract: Regression adjustment for the propensity score is a statistical method that reduces confounding from measured variables in observational data. A Bayesian propensity score analysis extends this idea by using simultaneous estimation of the propensity scores and the treatment effect. In this article, we conduct an empirical investigation of the performance of Bayesian propensity scores in the context of an observational study of the effectiveness of beta-blocker therapy in heart failure patients. We study the balancing properties of the estimated propensity scores. Traditional Frequentist propensity scores focus attention on balancing covariates that are strongly associated with treatment. In contrast, we demonstrate that Bayesian propensity scores can be used to balance the association between covariates and the outcome. This balancing property has the effect of reducing confounding bias because it reduces the degree to which covariates are outcome risk factors.
Straus S, Haynes RB. Managing evidence-based knowledge: the need for reliable, relevant and readable resources. CMAJ. 2009;180(9):942-945. Excerpt: One method for finding useful evidence is the "5S approach". This framework provides a model for the organization of evidence-based information services. Ideally, resources become more reliable, relevant and readable as one moves up the pyramid. To optimize search efficiency, it is best to start at the top of the pyramid and work down when trying to answer a clinical question. Available at: http://www.cmaj.ca/cgi/content/full/180/9/942 [Accessed September 9, 2009].
Mathieu S, Boutron I, Moher D, Altman DG, Ravaud P. Comparison of Registered and Published Primary Outcomes in Randomized Controlled Trials. JAMA. 2009;302(9):977-984. Comment: Only the abstract is freely available today (September 3, 2009), but if the full article is consistent with the abstract, this is a very shocking finding. Most registered trials are ambiguous about the primary outcome measure, and many of the trials that are not show a major discrepancy between the primary outcome as reported in the publication versus the primary outcome specified in the registry. Available at: http://jama.ama-assn.org/cgi/content/abstract/302/9/977 [Accessed September 3, 2009].
Poses R. A New Perspective on Evaluating the Effects of Financial Conflict of Interest on Research. Excerpt: I just posted about an article from the August issue of the Journal of Epidemiology and Community Health (link here, requires subscription.) Health Care Renewal readers may want to peruse this issue, which has some very interesting articles on conflicts of interest and related issues in research. In particular, an article by Prof Sander Greenland offers a fresh discussion based on perspectives from epidemiology, statistics, and cognitive psychology of the effects of financial conflicts of interest (COI) on (clinical, epidemiological, and health services) research (Greenland S. Accounting for uncertainty about investigator bias: disclosure is informative. J Epidemiol Community Health 2009; 63: 593-598. Link here, requires subscription.) Since only subscribers can easily get this article, and because of its importance, let me summarize its main points and provide appropriate quotations. Available at: http://hcrenewal.blogspot.com/2009/09/new-perspective-on-evaluating-effects.html [Accessed September 3, 2009].
Brody H. Fairness in Enforcing COI Regs by Journals, and Many Other Things Also. Excerpt: Laurence J. Hirsch, MD used to manage the Medical Communications Department for clinical research publications at Merck (2001-2006). He now works for a device company. This post concerns a paper he just published in the Mayo Clinic Proceedings. Available at: http://brodyhooked.blogspot.com/2009/09/fairness-in-enforcing-coi-regs-by.html [Accessed September 3, 2009].
Hirsch LJ. Conflicts of Interest, Authorship, and Disclosures in Industry-Related Scientific Publications: The Tort Bar and Editorial Oversight of Medical Journals. Mayo Clinic Proceedings. 2009;84(9):811-821. Excerpt: In recent years, Mayo Clinic Proceedings has published a variety of articles dealing with important, broad-reaching matters of societal interest that impact medicine and patient care. Topics included ideal physician behaviors, gender and medical career mentoring, advance directives and end-of-life issues, physician involvement in capital punishment, and, germane to this article, institutional conflicts of interest (COIs), as well as the journal's approach to publication of industry-sponsored clinical research. Equally important to the well-being of patients and of medicine is the legitimacy of interactions between industry sponsors of research and investigator-authors who communicate the information and the journals/editors who review and ultimately determine publication of the material. In this age of transparency, disclosure of COIs has assumed great prominence in medical journals. However, transparency is not always clear, disclosure policies are varied, and their implementation (by journals and medical societies) is asymmetric and biased. This commentary examines some prominent recent actions by consultants to plaintiffs' attorneys and a series of publications in 3 top-tier general medical journals that illustrate selective and incomplete disclosure of conflicts—both financial and otherwise. In my view, these events call into question actions by a medical specialty society with one of the consultants and, more broadly, the editorial practices at the journals concerning COIs. Specific recommendations are offered to address the latter. Available at: http://www.mayoclinicproceedings.com/content/84/9/811.short [Accessed September 3, 2009].
Lanier WL. Bidirectional Conflicts of Interest Involving Industry and Medical Journals: Who Will Champion Integrity? Mayo Clinic Proceedings. 2009;84(9):771-775. Excerpt: In the current issue of the Proceedings, the journal adds to its collection one more COI article that has passed the journal's stringent peer-review standards. In his commentary, Dr Laurence Hirsch, a part-time practicing endocrinologist, former employee of Merck & Co and current employee of another biomedical company contributor to the Pharmaceutical Manufacturers Association (PhRMA) guidelines on publication standards, and former president of the International Society for Medical Publishing Professionals (ISMPP), argues that journals and journal editors have compromised their credibility as adjudicators of COI and, although likely unintentionally, have abetted plaintiffs' lawyers to the detriment of the pharmaceutical industry. Specifically, Hirsch argues that journal editors sometimes use one set of COI standards for accepting or rejecting manuscripts when it suits their purposes and another set of standards when it does not. Available at: http://www.mayoclinicproceedings.com/content/84/9/771.short [Accessed September 3, 2009].
Wang R, Lagakos SW, Ware JH, Hunter DJ, Drazen JM. Statistics in Medicine -- Reporting of Subgroup Analyses in Clinical Trials. N Engl J Med. 2007;357(21):2189-2194. Excerpt: Medical research relies on clinical trials to assess therapeutic benefits. Because of the effort and cost involved in these studies, investigators frequently use analyses of subgroups of study participants to extract as much information as possible. Such analyses, which assess the heterogeneity of treatment effects in subgroups of patients, may provide useful information for the care of patients and for future research. However, subgroup analyses also introduce analytic challenges and can lead to overstated and misleading results. This report outlines the challenges associated with conducting and reporting subgroup analyses, and it sets forth guidelines for their use in the Journal. Although this report focuses on the reporting of clinical trials, many of the issues discussed also apply to observational studies. Available at: http://content.nejm.org/cgi/content/full/357/21/2189 [Accessed September 3, 2009].

August
Kolata G. Lack of Study Volunteers Hobbles Cancer Fight. The New York Times. 2009. Excerpt: "There are more than 6,500 cancer clinical trials seeking adult patients, according to clinicaltrials.gov, a trials registry. But many will be abandoned along the way. More than one trial in five sponsored by the National Cancer Institute failed to enroll a single subject, and only half reached the minimum needed for a meaningful result, Dr. Ramsey and his colleague John Scoggins reported in an editorial in the September 2008 issue of The Oncologist." Available at: www.nytimes.com/2009/08/03/health/research/03trials.html [Accessed August 29, 2009].
Pearson R, Liu X, Sanguinetti G, et al. puma: a Bioconductor package for propagating uncertainty in microarray analysis. BMC Bioinformatics. 2009;10(1):211. Excerpt: Background Most analyses of microarray data are based on point estimates of expression levels and ignore the uncertainty of such estimates. By determining uncertainties from Affymetrix GeneChip data and propagating these uncertainties to downstream analyses it has been shown that we can improve results of differential expression detection, principal component analysis and clustering. Previously, implementations of these uncertainty propagation methods have only been available as separate packages, written in different languages. Previous implementations have also suffered from being very costly to compute, and in the case of differential expression detection, have been limited in the experimental designs to which they can be applied. Results puma is a Bioconductor package incorporating a suite of analysis methods for use on Affymetrix GeneChip data. puma extends the differential expression detection methods of previous work from the 2-class case to the multi-factorial case. puma can be used to automatically create design and contrast matrices for typical experimental designs, which can be used both within the package itself but also in other Bioconductor packages. The implementation of differential expression detection methods has been parallelised leading to significant decreases in processing time on a range of computer architectures. puma incorporates the first R implementation of an uncertainty propagation version of principal component analysis, and an implementation of a clustering method based on uncertainty propagation. All of these techniques are brought together in a single, easy-to-use package with clear, task-based documentation. Available at: www.biomedcentral.com/1471-2105/10/211 [Accessed August 19, 2009].
Harrell FE. Statistical Graphics Course. Available at: biostat.mc.vanderbilt.edu/wiki/Main/StatGraphCourse [Accessed August 18, 2009]. Excerpt: Graphical methods are being increasingly used for exploratory data analysis. Some of the many graphical tools that are useful in this setting are scatterplot matrices, nonparametric smoothers, and tree diagrams. Statistical graphics for presenting information have been used much longer, but most of the commonly used graphics used in papers, presentations, and the popular media, such as bar charts and pie charts, are either poor or misleading in communicating information to the reader. This short course begins with a series of graphical horror stories from the scientific and lay press. Then elements of graphical perception and good graph construction, many from the writings of Bill Cleveland, are covered. Practical suggestions for choosing the best chart or graph type, making good and clear graphics, and formatting are covered. Techniques for simultaneous presentation of multiple variables are described.
Burns P. Spreadsheet Addiction. Available at: www.burns-stat.com/pages/Tutor/spreadsheet_addiction.html [Accessed August 18, 2009]. Excerpt: The goal of computing is not to get an answer, but to get the correct answer. Often a wrong answer is much worse than no answer at all. There are a number of features of spreadsheets that present a challenge to error-free computing.
Deffeyes J, Harbourne R, Dejong S, et al. Use of information entropy measures of sitting postural sway to quantify developmental delay in infants. Journal of NeuroEngineering and Rehabilitation. 2009;6(1):34. Available at: www.jneuroengrehab.com/content/6/1/34 [Accessed August 18, 2009].
Herber O, Schnepp W, Rieger M. Recruitment rates and reasons for community physicians' non-participation in an interdisciplinary intervention study on leg ulceration. BMC Medical Research Methodology. 2009;9(1):61. Available at: www.biomedcentral.com/1471-2288/9/61 [Accessed August 18, 2009]. Excerpt: Despite great efforts to recruit physicians, the recruitment rate reached only 26 out of 1549 contacted practices (1.7%) and 12 out of 273 (4.4%) practices during the first and second recruitment phase respectively. The overall recruitment rate over the 16-month recruitment period was 2%. With a target recruitment rate of n=300, only 45 patients were enrolled in the study, not meeting study projections.
Moreno SG, Sutton AJ, Turner EH, et al. Novel methods to deal with publication biases: secondary analysis of antidepressant trials in the FDA trial registry database and related journal publications. BMJ. 2009;339(aug07_1):b2981. Available at: www.bmj.com/cgi/content/abstract/339/aug07_1/b2981 [Accessed August 8, 2009]. Excerpt: Methods Publication biases were identified using novel contour enhanced funnel plots, a regression based adjustment method, Egger’s test, and the trim and fill method. Results were compared with a meta-analysis of the gold standard data submitted to the FDA. Results Severe asymmetry was observed in the contour enhanced funnel plot that appeared to be heavily influenced by the statistical significance of results, suggesting publication biases as the cause of the asymmetry. Applying the regression based adjustment method to the journal data produced a similar pooled effect to that observed by a meta-analysis of the FDA data. Contrasting journal and FDA results suggested that, in addition to other deviations from study protocol, switching from an intention to treat analysis to a per protocol one would contribute to the observed discrepancies between the journal and FDA results.

July
Osborne JW, Holland A. What is authorship, and what should it be? A survey of prominent guidelines for determining authorship in scientific publications. Practical Assessment, Research & Evaluation. 2009;14(15). Available at pareonline.net/pdf/v14n15.pdf. Excerpt: The goal of this paper is to review prominent and diverse guidelines concerning scientific authorship and to attempt to synthesize existing guidelines into recommendations that represent ethical practices for ensuring credit where (and only where) credit is due.
Redelmeier DA. The Cognitive Psychology of Missed Diagnoses. Ann Intern Med. 2005;142(2):115-120. Available at: www.annals.org/cgi/content/abstract/142/2/115 [Accessed July 8, 2009]. Description: this paper presents a case study and discusses many of the psychological issues that come into play during the process of establishing a diagnosis.

June
Ward A. The role of causal criteria in causal inferences: Bradford Hill's "aspects of association". Epidemiologic Perspectives & Innovations. 2009;6(1):2. Available at: www.epi-perspectives.com/content/6/1/2 [Accessed June 24, 2009]. Abstract: As noted by Wesley Salmon and many others, causal concepts are ubiquitous in every branch of theoretical science, in the practical disciplines and in everyday life. In the theoretical and practical sciences especially, people often base claims about causal relations on applications of statistical methods to data. However, the source and type of data place important constraints on the choice of statistical methods as well as on the warrant attributed to the causal claims based on the use of such methods. For example, much of the data used by people interested in making causal claims come from non-experimental, observational studies in which random allocations to treatment and control groups are not present. Thus, one of the most important problems in the social and health sciences concerns making justified causal inferences using non-experimental, observational data. In this paper, I examine one method of justifying such inferences that is especially widespread in epidemiology and the health sciences generally - the use of causal criteria. I argue that while the use of causal criteria is not appropriate for either deductive or inductive inferences, they do have an important role to play in inferences to the best explanation. As such, causal criteria, exemplified by what Bradford Hill referred to as "aspects of [statistical] associations", have an indispensible part to play in the goal of making justified causal claims.

May
Lazic S, Mason S, Michell A, Barker R. Visualising disease progression on multiple variables with vector plots and path plots. BMC Medical Research Methodology. 2009;9(1):32. Available at: www.biomedcentral.com/1471-2288/9/32 [Accessed May 29, 2009]. Description: This paper shows how to use vector plots to display longitudinal changes in individual patients.
SAS Institute. Ten Great Reasons Why A Statistician Should Update to SAS 9.2. Available at: support.sas.com/rnd/app/da/stat_top10.html [Accessed May 26, 2009]. Description: I have not used SAS in ten years, but it helps to know what I am missing. The latest version of SAS has generalized linear mixed models, quantile regression, and Markov Chain Monte Carlo solutions for several procedures. SAS has also implemented certain model selection approaches like LAR and LASSO.
American Statistical Association. Making Sense of Statistical Studies. Available at: http://www.amstat.org/education/msss/?nl=0509 [Accessed May 20, 2009]. Excerpt: Are hot dogs unhealthy? What percent of people wear their seat belts when driving? Which works better-a low-fat diet or a low-carbohydrate diet? Would most teenagers return an extra $10 they received in incorrect change at a store? Does listening to music hurt students' concentration and ability to study? How are peoples' heights and foot lengths related? These are just a few examples of the types of questions students will explore in Making Sense of Statistical Studies (MSSS). The module consists of 15 hands-on investigations that provide students with valuable experience in designing and analyzing statistical studies. It is written for an upper middle-school or high-school audience having some background in exploratory data analysis and basic probability.
Gunnes N, Seierstad T, Aamdal S, et al. Assessing quality of life in a randomized clinical trial: Correcting for missing data. BMC Medical Research Methodology. 2009;9(1):28. Available at: www.biomedcentral.com/1471-2288/9/28 [Accessed May 20, 2009]. Excerpt: Use of proper methodology developed for analysing data subject to missingness is necessary to reduce potential estimation bias. The quality of life of patients receiving radiation therapy with concurrent chemotherapy (docetaxel) appears somewhat worse than that of patients receiving radiation therapy alone in the period during which treatment is given. The conclusions are robust for the choice of statistical methods.
Mills E, Chan A, Wu P, et al. Design, analysis, and presentation of crossover trials. Trials. 2009;10(1):27. Available at: www.trialsjournal.com/content/10/1/27 [Accessed May 20, 2009]. Excerpt: Reports of crossover trials frequently omit important methodological issues in design, analysis, and presentation. Guidelines for the conduct and reporting of crossover trials might improve the conduct and reporting of studies using this important trial design.
Coory M, Wills R, Barnett A. Bayesian versus frequentist statistical inference for investigating a one-off cancer cluster reported to a health depart- ment. BMC Medical Research Methodology. 2009;9(1):30. Available at: www.biomedcentral.com/1471-2288/9/30 [Accessed May 19, 2009].
Elhai JD, Calhoun PS, Ford JD. Statistical procedures for analyzing mental health services data. Psychiatry Research. 2008;160(2):129-136. Available at: www.ncbi.nlm.nih.gov/pubmed/18585790 [Accessed May 19, 2009].

April
Flom PL, Cassell DL. Stopping stepwise: Why stepwise and similar selection methods are bad, and what you should use. Available at: www.nesug.org/proceedings/nesug07/sa/sa07.pdf [Accessed April 24, 2009].
Moerman C, Deurenberg R, Haafkens J. Locating sex-specific evidence on clinical questions in MEDLINE: a search filter for use on OvidSPTM. BMC Medical Research Methodology. 2009;9(1):25. Available at: www.biomedcentral.com/1471-2288/9/25 [Accessed April 16, 2009]. Abstract: Background Many recently published clinical studies report sex-specific data. This information may help to improve clinical decision-making for both sexes, but it is not easily accessible in MEDLINE. The aim of this project was to develop and validate a search filter that would facilitate the retrieval of studies reporting high quality sex-specific data on clinical questions. Methods A filter was developed by screening titles, abstracts and Medical Subject Headings (MeSH) in a set of 80 high quality and relevant papers, 75 of which were identified through a review of clinical guidelines and five through other means. The filter, for use on OvidSPTM, consists of nine command lines for searching free text words in the title, abstract and MeSH of a paper. It was able to identify 74/80 (92.5%) of the articles from which it was derived. The filter was evaluated in a set of 622 recently published original studies on Alzheimer's disease and on asthma. It was validated against a reference of 98 studies from this set, which provided high quality, clinically relevant, sex-specific evidence. Recall and precision were used as performance measures. Results The filter demonstrated 81/98 (83%) recall and 81/125 (65%) precision in retrieving relevant articles on Alzheimer's disease and on asthma. In comparison, only 30/98 (31%) recall would have been achieved if sex-specific MeSH terms only had been used. Conclusion This sex-specific search filter performs well in retrieving relevant papers, while its precision rate is good. It performs better than a search with sex-specific MeSH. The filter can be useful to anyone seeking sex-specific clinical evidence (e.g., guideline organizations, researchers, medical educators, clinicians)
Ethgen M, Boutron I, Steg PG, Roy C, Ravaud P. Quality of reporting internal and external validity data from randomized controlled trials evaluating stents for percutaneous coronary intervention. BMC Medical Research Methodology. 2009;9(1):24. Available at: www.biomedcentral.com/1471-2288/9/24 [Accessed April 16, 2009]. Abstract: Background Stents are commonly used to treat patients with coronary artery disease. However, the quality of reporting internal and external validity data in published reports of randomised controlled trials (RCTs) of stents has never been assessed. The objective of our study was to evaluate the quality of reporting internal and external validity data in published reports of RCTs assessing the stents for percutaneous coronary interventions. Methods A systematic literature review was conducted. Reports of RCTs assessing stents for percutaneous coronary interventions indexed in MEDLINE and the Cochrane Central Register of Controlled Trials and published between January 2003 and September 2008 were selected. A standardized abstraction form was used to extract data. All analyses were adjusted for the effect of clustering articles by journal. Results 132 articles were analyzed. The generation of the allocation sequence was adequate in 58.3% of the reports; treatment allocation was concealed in 34.8%. Adequate blinding was reported in one-fifth of the reports. An intention-to-treat analysis was described in 79.5%. The main outcome was a surrogate angiographic endpoint in 47.0%. The volume of interventions per center was described in two reports. Operator expertise was described in five (3.8%) reports. The quality of reporting was better in journals with high impact factors and in journals endorsing the CONSORT statement. Conclusions The current reporting of results of RCTs testing stents needs to be improved to allow readers to appraise the risk of bias and the applicability of the results.
Wuensch K. Stepwise Regression = Voodoo Regression. Available at: core.ecu.edu/psyc/wuenschk/StatHelp/Stepwise-Voodoo.htm [Accessed April 16, 2009]. Excerpt: It is pretty cool, but not necessarily very useful, and just plain dangerous in the hands of somebody not well educated in the multiple regression techniques, including effects of collinearity, redundancy, and suppression. Here are some quotes from others I have collected from the now departed STAT-L.
Shahen B. Orwik : The Open Science Platform. Available at: orwik.blogspot.com/ [Accessed April 16, 2009].

March
Jefferson T, Di Pietrantonj C, Debalini MG, Rivetti A, Demicheli V. Relation of study quality, concordance, take home message, funding, and impact in studies of influenza vaccines: systematic review. BMJ. 2009;338(feb12_2):b354. Available at: www.bmj.com/cgi/content/abstract/338/feb12_2/b354 [Accessed March 31, 2009].
Pogue D. Should You Worry About Data Rot? The New York Times. 2009. Available at: www.nytimes.com/2009/03/26/technology/personaltech/26pogue-email.html [Accessed March 30, 2009]. Description: There are some physical aspects to the data that you store. these can affect whether your data is readable 10 or 20 years later. David Pogue interviews Dag Spicer, an expert on the durability (or lack thereof) of various storage media.
Broeze K, Opmeer B, Bachmann L, et al. Individual patient data meta-analysis of diagnostic and prognostic studies in obstetrics, gynaecology and reproductive medicine. BMC Medical Research Methodology. 2009;9(1):22. Available at: www.biomedcentral.com/1471-2288/9/22 [Accessed March 30, 2009]. Abstract: Background In clinical practice a diagnosis is based on a combination of clinical history, physical examination and additional diagnostic tests. At present, studies on diagnostic research often report the accuracy of tests without taking into account the information already known from history and examination. Due to this lack of information, together with variations in design and quality of studies, conventional meta-analyses based on these studies will not show the accuracy of the tests in real practice. By using individual patient data (IPD) to perform meta-analyses, the accuracy of tests can be assessed in relation to other patient characteristics and allows the development or evaluation of diagnostic algorithms for individual patients. In this study we will examine these potential benefits in four clinical diagnostic problems in the field of gynaecology, obstetrics and reproductive medicine. Methods Based on earlier systematic reviews for each of the four clinical problems, studies are considered for inclusion. The first authors of the included studies will be invited to participate and share their original data. After assessment of validity and completeness, the acquired datasets are merged. Based on these data, a series of analyses will be performed, including a systematic comparison of the results of the IPD meta-analysis with those of a conventional meta-analysis, development of multivariable models for clinical history alone and for the combination of history, physical examination and relevant diagnostic tests, and development of clinical prediction rules for individual patients. These will be made accessible for clinicians. Discussion The use of IPD meta-analysis will allow evaluating accuracy of diagnostic tests in relation to other relevant information. Ultimately, this could increase the efficiency of the diagnostic work-up, e.g. by reducing the need for invasive tests and/or improving the accuracy of the diagnostic workup. This study will assess whether these benefits of IPD meta-analysis over conventional meta-analysis can be exploited and will provide a framework for future IPD meta-analyses in diagnostic research.
Neal R. Radford Neal’s blog. Available at: radfordneal.wordpress.com/ [Accessed March 13, 2009].
Smith D. Revolutions. News about R, statistics and the world of open source from the staff of REvolution Computing. Available at: blog.revolution-computing.com/ [Accessed March 13, 2009].
Sonego P. One R Tip A Day. Available at: onertipaday.blogspot.com/ [Accessed March 13, 2009].
Xie Y. Keep on Fighting! - Yihui XIE: A Blog Site for Statistics. Available at: www.yihui.name/en/index.php [Accessed March 13, 2009].
Goozner M. GoozNews: States Say Medscape CME Part of Off-Label Promotion Scheme. Available at: www.gooznews.com/archives/001345.html [Accessed March 9, 2009].
Goodyear M. Unintended results of research. Harm Reduction Journal. 6(5). Available at: www.harmreductionjournal.com/content/6/1/5/comments#336610 [Accessed March 9, 2009].
Eurich D, Tsuyuki R, Majumdar S, et al. Metformin treatment in diabetes and heart failure: when academic equipoise meets clinical reality. Trials. 2009;10(1):12. Available at: www.trialsjournal.com/content/10/1/12 [Accessed March 9, 2009].
Rico-Villademoros F, Hernando T, Sanz J, et al. The role of the clinical research coordinator - data manager - in oncology clinical trials. BMC Medical Research Methodology. 2004;4(1):6. Available at: www.biomedcentral.com/1471-2288/4/6 [Accessed March 3, 2009].
Tierney J, Stewart L, Ghersi D, Burdett S, Sydes M. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials. 2007;8(1):16. Available at: www.trialsjournal.com/content/8/1/16 [Accessed March 3, 2009].

February
Holland K. Smoothing the Way to Self-Employment. The New York Times. 2009. Available at: www.nytimes.com/2009/02/22/jobs/22mgmt.html [Accessed February 26, 2009].
Chan A, Hrobjartsson A, Haahr MT, Gotzsche PC, Altman DG. Empirical Evidence for Selective Reporting of Outcomes in Randomized Trials: Comparison of Protocols to Published Articles. JAMA. 2004;291(20):2457-2465. Available at: jama.ama-assn.org/cgi/content/abstract/291/20/2457 [Accessed February 25, 2009].
Chan A, Altman DG. Identifying outcome reporting bias in randomised trials on PubMed: review of publications and survey of authors. BMJ. 2005;330(7494):753. Available at: www.bmj.com/cgi/content/abstract/330/7494/753 [Accessed February 25, 2009].
Chan A, Krleza-Jeric K, Schmid I, Altman DG. Outcome reporting bias in randomized trials funded by the Canadian Institutes of Health Research. CMAJ. 2004;171(7):735-740. Available at: www.cmaj.ca/cgi/content/abstract/171/7/735 [Accessed February 25, 2009].
Feinman R. Intention-to-treat. What is the question? Nutrition & Metabolism. 2009;6(1):1. Available at: www.nutritionandmetabolism.com/content/6/1/1 [Accessed February 24, 2009].
Johnston M, Hays R, Hui K. Evidence-based effect size estimation: An illustration using the case of acupuncture for cancer-related fatigue. BMC Complementary and Alternative Medicine. 2009;9(1):1. Available at: www.biomedcentral.com/1472-6882/9/1 [Accessed February 24, 2009].
Rancoita P, Hutter M, Bertoni F, Kwee I. Bayesian DNA copy number analysis. BMC Bioinformatics. 2009;10(1):10. Available at: www.biomedcentral.com/1471-2105/10/10 [Accessed February 24, 2009].
Martin-Requena V, Munoz-Merida A, Claros M, Trelles O. PreP+07: improvements of a user friendly tool to pre-process and analyse microarray data. BMC Bioinformatics. 2009;10(1):16. Available at: www.biomedcentral.com/1471-2105/10/16 [Accessed February 24, 2009].
Moreno S, Sutton A, Ades A, et al. Assessment of regression-based methods to adjust for publication bias through a comprehensive simulation study. BMC Medical Research Methodology. 2009;9(1):2. Available at: www.biomedcentral.com/1471-2288/9/2 [Accessed February 24, 2009].
Haynes AB, Weiser TG, Berry WR, et al. A Surgical Safety Checklist to Reduce Morbidity and Mortality in a Global Population. N Engl J Med. 2009;360(5):491-499. Available at: content.nejm.org/cgi/content/abstract/360/5/491 [Accessed February 24, 2009].
Gaye P, Nelson D. Effective scale-up: avoiding the same old traps. Human Resources for Health. 2009;7(1):2. Available at: www.human-resources-health.com/content/7/1/2 [Accessed February 24, 2009].
Yu H, Agarwal S, Johnston M, Cohen A. Are figure legends sufficient? Evaluating the contribution of associated text to biomedical figure comprehension. Journal of Biomedical Discovery and Collaboration. 2009;4(1):1. Available at: www.j-biomed-discovery.com/content/4/1/1 [Accessed February 23, 2009].
Hirji K. No short-cut in assessing trial quality: a case study. Trials. 2009;10(1):1. Available at: www.trialsjournal.com/content/10/1/1 [Accessed February 23, 2009].
Lund I, Naslund J, Lundeberg T. Minimal acupuncture is not a valid placebo control in randomised controlled trials of acupuncture: a physiologist's perspective. Chinese Medicine. 2009;4(1):1. Available at: www.cmjournal.org/content/4/1/1 [Accessed February 10, 2009].
Cao J, Xie X, Zhang S, Whitehurst A, White M. Bayesian optimal discovery procedure for simultaneous significance testing. BMC Bioinformatics. 2009;10(1):5. Available at: www.biomedcentral.com/1471-2105/10/5 [Accessed February 23, 2009].
Vittinghoff E, McCulloch CE. Relaxing the Rule of Ten Events per Variable in Logistic and Cox Regression. Am. J. Epidemiol. 2007;165(6):710-718. Available at: aje.oxfordjournals.org/cgi/content/abstract/165/6/710 [Accessed February 18, 2009]. Description: This article examines the rule that you need 10 events per independent variable. Some sources cite 15 events and other 20 events per independent variable. The authors argue that in the context of adjusting for confounders, this rule might be relaxed a bit.
SAS Institute. 30333 - FASTats: Frequently Asked-For Statistics. Usage Note 30333: FASTats: Frequently Asked-For Statistics. Available at: support.sas.com/kb/30/333.html [Accessed February 11, 2009]. Description: This webpage lists hundreds of specialized statistics and explains how to compute them using SAS software.

January
Mills E, Rachlis B, O'Regan C, Thabane L, Perri D. Metastatic renal cell cancer treatments: An indirect comparison meta-analysis. BMC Cancer. 2009;9(1):34. Available at: www.biomedcentral.com/1471-2407/9/34 [Accessed January 30, 2009]. Description: This paper is an illustrative example of the use of meta-analysis to compare two interventions when the interventions are not compared directly to one another in any study, but instead are compared to a third intervention common to all the studies.
Schluter P. A multivariate hierarchical Bayesian approach to measuring agreement in repeated measurement method comparison studies. BMC Medical Research Methodology. 2009;9(1):6. Available at: www.biomedcentral.com/1471-2288/9/6 [Accessed January 30, 2009]. Description: This paper considers a Bayesian extension to the Bland-Altman chart to incorporate repeatability assessment as well as agreement among three or more methods.
Koelch M, Singer H, Prestel A, et al. "...because I am something special" or "I think I will be something like a guinea pig": information and assent of legal minors in clinical trials - assessment of understanding, appreciation and reasoning. Child and Adolescent Psychiatry and Mental Health. 2009;3(1):2. Available at: www.capmh.com/content/3/1/2 [Accessed January 30, 2009]. Description: Children do not have the legal capacity to formally consent to participate in research. Respect for the individual, however, still requires us to seek assent from a child before they participate. How much can a child truly understand about the research hypothesis? This study examined a group of children between the ages of 7 and 15 diagnosed with attention deficit/hyperactivity disorder (ADHD) or ADHD combined with oppositional defiant disorder. Children understood the general procedures being conducted in the research but had more difficulty with abstract concepts such as the need for a placebo and their individual chance of receiving a placebo.
Abrahamowicz M, du Berger R, Krewski D, et al. Bias due to Aggregation of Individual Covariates in the Cox Regression Model. Am. J. Epidemiol. 2004;160(7):696-706. Available at: aje.oxfordjournals.org/cgi/content/abstract/160/7/696 [Accessed January 19, 2009]. Description: Aggregated covariates represent covariates measured at a group level such as an average income for all patients with a certain zip code. Aggregated covariates are convenient, inexpensive, and often can help protect patient confidentiality, but they have their limitations. This article discusses problems associated with aggregated covariates in the cox regression model.
Harrell FE. The Role of Covariable Adjustment in the Analysis of Clinical Trials. Available at: biostat.mc.vanderbilt.edu/twiki/pub/Main/FHHandouts/covadj.pdf [Accessed January 19, 2009]. Presented at the Statistics of Multi-center Trials, Henry Stewart Conference Studies, Washington DC, September 14, 2001. Note that this is a PDF of some Powerpoint slides, which I usually do not like to include, but the reputation of Dr. Harrell and the quality of the bibliograpy more than compensate.
Trevor Sheldon. Managing uncertainty in healthcare. Report of a meeting organised by NICE and AHRQ. 2008. Available at: www.nice.org.uk/media/A1A/E6/NICEAHRQWorkshopReportFINAL.pdf [Accessed January 15, 2009]. Excerpt: There are certain challenges that confront virtually all health systems, irrespective of the means by which they are funded and administered. One such is the management of uncertainty: specifically, knowing what to do when data on the effectiveness or the cost-effectiveness of new medicines or procedures is incomplete or inadequate, but decisions have nonetheless to be taken on whether to purchase and supply them to patients. A similar issue arises when there is suspicion that a procedure or medicine already in use may be relatively ineffective or represent poor value for money.
R. Kabacoff. Quick-R: Home Page. Accessed on 2009-01-07. Excerpt: R is an elegant and comprehensive statistical and graphical programming language. Unfortunately, it can also have a steep learning curve. I created this website for experienced users of popular statistical packages such as SAS, SPSS, Stata, and Systat (although current R users should also find it useful). My goal is to help you quickly access this language in your work. URL: www.statmethods.net
Vance A. Data Analysts Captivated by R’s Power. The New York Times. 2009. Available at: www.nytimes.com/2009/01/07/technology/business-computing/07program.html [Accessed January 7, 2009]. Excerpt: To some people R is just the 18th letter of the alphabet. To others, it’s the rating on racy movies, a measure of an attic’s insulation or what pirates in movies say. R is also the name of a popular programming language used by a growing number of data analysts inside corporations and academia. It is becoming their lingua franca partly because data mining has entered a golden age, whether being used to set ad prices, find new drugs more quickly or fine-tune financial models. Companies as diverse as Google, Pfizer, Merck, Bank of America, the InterContinental Hotels Group and Shell use it.
Mioplanet, Pixel Ruler: Your free virtual screen ruler. Accessed on 2009-01-05. Description: I try to keep my graphic images on my website to about 400 pixels in width. This free utility places a ruler on the screen so I can size my graphic images appropriately before exporting them to my website. URL: www.mioplanet.com/products/pixelruler
Wolfe R, Hanley J. If we're so different, why do we keep overlapping? When 1 plus 1 doesn't make 2. CMAJ. 2002;166(1):65-66. Available at: www.cmaj.ca/cgi/content/full/166/1/65 [Accessed January 5, 2009]. Description: This article provides a simple explanation why two overlapping confidence intervals is not the same as showing that the two means are not statistically different from one another.
Rucker G, Schwarzer G, Carpenter J, Schumacher M. Undue reliance on I^2 in assessing heterogeneity may mislead. BMC Medical Research Methodology. 2008;8(1):79. Available at: www.biomedcentral.com/1471-2288/8/79 [Accessed January 2, 2009]. This article describes several quantitative measures of heterogeneity, and argues that most of these measures, including I^2, are dependent on the sample sizes of the original studies. Instead of I^2, the authors recommend the use of tau^2.

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