P.Mean: Interesting articles, books, quotes, or websites added to this site for 2008 (created 2008-11-17)

This page is moving to several different pages:

Zotero.

Regression with SAS.

Health statistics.

Zotero.

Placebo effects.

Clinical Practice Guidelines.

Four assumptions.

Intervening variables.

Variables and hypotheses.

Please also consult the page for other years:

December

  1. Zotero: The Next Generation Research Tool. George Mason University. Excerpt: Zotero is an easy-to-use yet powerful research tool that helps you gather, organize, and analyze sources (citations, full texts, web pages, images, and other objects), and lets you share the results of your research in a variety of ways. An extension to the popular open-source web browser Firefox, Zotero includes the best parts of older reference manager software (like EndNote)—the ability to store author, title, and publication fields and to export that information as formatted references—and the best parts of modern software and web applications (like iTunes and del.icio.us), such as the ability to interact, tag, and search in advanced ways. Zotero integrates tightly with online resources; it can sense when users are viewing a book, article, or other object on the web, and—on many major research and library sites—find and automatically save the full reference information for the item in the correct fields. Since it lives in the web browser, it can effortlessly transmit information to, and receive information from, other web services and applications; since it runs on one’s personal computer, it can also communicate with software running there (such as Microsoft Word). And it can be used offline as well (e.g., on a plane, in an archive without WiFi). URL: www.zotero.org

    November
     
  2. Regression with SAS. Chapter 5: Additional coding systems for categorical variables in regression analysis. Xiao Chen, Phil Ender, Michael Mitchell, Christine Wells, UCLA Academic Technology Services. Excerpt: Categorical variables require special attention in regression analysis because, unlike dichotomous or continuous variables, they cannot by entered into the regression equation just as they are. For example, if you have a variable called race that is coded 1 = Hispanic, 2 = Asian 3 = Black 4 = White, then entering race in your regression will look at the linear effect of race, which is probably not what you intended. Instead, categorical variables like this need to be recoded into a series of variables which can then be entered into the regression model. There are a variety of coding systems that can be used when coding categorical variables. Ideally, you would choose a coding system that reflects the comparisons that you want to make. In Chapter 3 of the Regression with SAS Web Book we covered the use of categorical variables in regression analysis focusing on the use of dummy variables, but that is not the only coding scheme that you can use. For example, you may want to compare each level to the next higher level, in which case you would want to use "forward difference" coding, or you might want to compare each level to the mean of the subsequent levels of the variable, in which case you would want to use "Helmert" coding. By deliberately choosing a coding system, you can obtain comparisons that are most meaningful for testing your hypotheses. This website was last verified on 2008-URL: www.ats.ucla.edu/stat/sas/webbooks/reg/chapter5/sasreg5.htm. Added 2008-11-19 to  Category: Analysis of variance.
  3. Helping Doctors and Patients Make Sense of Health Statistics. Gerd Gigerenzer Wolfgang Gaissmaier Elke Kurz-Milcke Lisa M. Schwartz Steven Woloshin. Psychological Science in the Public Interest 2008: 8(2); 53-96. [Abstract] [PDF]. Excerpt: Many doctors, patients, journalists, and politicians alike do not understand what health statistics mean or draw wrong conclusions without noticing. Collective statistical illiteracy refers to the widespread inability to understand the meaning of numbers. For instance, many citizens are unaware that higher survival rates with cancer screening do not imply longer life, or that the statement that mammography screening reduces the risk of dying from breast cancer by 25% in fact means that 1 less woman out of 1,000 will die of the disease. We provide evidence that statistical illiteracy (a) is common to patients, journalists, and physicians; (b) is created by nontransparent framing of information that is sometimes an unintentional result of lack of understanding but can also be a result of intentional efforts to manipulate or persuade people; and (c) can have serious consequences for health. Added 2008-11-18 to Category: Critical appraisal.
  4. Components of placebo effect: randomised controlled trial in patients with irritable bowel syndrome. T. J. Kaptchuk, J. M. Kelley, L. A. Conboy, R. B. Davis, C. E. Kerr, E. E. Jacobson, I. Kirsch, R. N. Schyner, B. H. Nam, L. T. Nguyen, M. Park, A. L. Rivers, C. McManus, E. Kokkotou, D. A. Drossman, P. Goldman, A. J. Lembo. Bmj 2008: 336(7651); 999-1003. [Medline] [Abstract] [Full text] [PDF]. Description: The authors suggest that the placebo affect can be separated into three components: the process of observation itself (the Hawthorne effect), the therapeutic ritual associated with a placebo, and the patient-practitioner interactions. They then test this empirically in a three arm single blind study. There were significant differences between the arms of the study, and the effect of the patient-practitioner interactions was the strongest effect. Added 2008-11-17 to Category: Placebos in research.

    Earlier (the dates that I added these entries are unknown)
     
  5. The Myth of Equipoise in Phase 1 Clinical Trials. Adil E. Shamoo, PhD. Posted 11/05/2008 at Medscape J Med. 2008;10(11):254. Note that a free registriation may be required. Excerpt: Phase 1 clinical research trials using healthy volunteers are conducted for the sole purpose of serving the public good (a utilitarian concept). The literature on equipoise analysis does not exclude phase 1 trials with controls or healthy volunteers from the claim of being in "equipoise." The continued perpetuation of this ethically and scientifically invalid concept undermines the ethics of research with human subjects. URL: www.medscape.com/viewarticle/582554
  6. Interesting quote: The statistician who supposes that his main contribution to the planning of an experiment will involve statistical theory, finds repeatedly that he makes his most valuable contribution simply by persuading the investigator to explain why he wishes to do the experiment, by persuading him to justify the experimental treatments, and to explain why it is that the experiment, when completed, will assist him in his research.  -- Gertrude M. Cox. (I can't recall the original source where I found this quote. Sorry!)
  7. Development of evidence-based clinical practice guidelines (CPGs): comparing approaches. Tari Turner, Marie Misso, Claire Harris, and Sally Green. Implementation Science 2008, 3:45doi:10.1186/1748-5908-3-45. [Abstract] [PDF] Description: This article identified publications on developing clinical practice guidelines. The review found six relevant publications. All these publications stressed the need for a multidisciplinary panel, consumer involvement, identification of clinical questions, systematic searches for evidence, consultation beyond the development group, and regular reviews and updates.
  8. Four assumptions of multiple regression that researchers should always test. Osborne, Jason & Elaine Waters (2002). Practical Assessment, Research & Evaluation, 8(2). Retrieved October 20, 2008 from PAREonline.net/getvn.asp?v=8&n=2. Excerpt: Most statistical tests rely upon certain assumptions about the variables used in the analysis. When these assumptions are not met the results may not be trustworthy, resulting in a Type I or Type II error, or over- or under-estimation of significance or effect size(s). As Pedhazur (1997, p. 33) notes, "Knowledge and understanding of the situations when violations of assumptions lead to serious biases, and when they are of little consequence, are essential to meaningful data analysis". However, as Osborne, Christensen, and Gunter (2001) observe, few articles report having tested assumptions of the statistical tests they rely on for drawing their conclusions. This creates a situation where we have a rich literature in education and social science, but we are forced to call into question the validity of many of these results, conclusions, and assertions, as we have no idea whether the assumptions of the statistical tests were met. Our goal for this paper is to present a discussion of the assumptions of multiple regression tailored toward the practicing researcher.
  9. Wikipedia: Intervening variable. Excerpt: An intervening variable is a hypothetical internal state that is used to explain relationships between observed variables, such as independent and dependent variables, in empirical research. An intervening variable facilitates a better understanding of the relationship between the independent and dependent variables when the variables appear to not have a definite connection. They are studied by means of operational definitions and have no existence apart. URL: en.wikipedia.org/wiki/Intervening_variable
  10. EDF 5841 Methods of Educational Research. Guide 2: Variables and Hypotheses. Susan Carol Losh, Florida State University, September 3, 2001. Description: This webpage provides simple definitions of terms commonly used in educational research such as intervening variable, conceptual hypothesis, and operational variables. URL: edf5481-01.fa01.fsu.edu/Guide2.html
  11. EDF 5841 Methods of Educational Research. Guide 3: Reliability, Validity, Causality, and Experiments. Susan Carol Losh, Florida State University, September 11, 2001. Description: This webpage provides simple definitions of terms commonly used in educational research such as construct validity and discusses how to establish a causal relationship. URL: edf5481-01.fa01.fsu.edu/Guide3.html
  12. EDF 5841Methods of Educational Research. Guide 5: A Survey Research Timetable. Susan Carol Losh, Florida State University, September 25, 2001. Description: This webpage outlines the steps you need to follow in a survey research study, with special emphasis on pilot testing. URL: edf5481-01.fa01.fsu.edu/Guide5.html
  13. EDF 5841 Methods of Educational Research. Guide 6: Focus Group Basics. Susan Carol Losh, Florida State University, September 25, 2001. Description: This webpage outlines the steps you need to follow in a survey research study, with special emphasis on pilot testing. URL: edf5481-01.fa01.fsu.edu/Guide6.html

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