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
- 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
-
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.
- 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.
- 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)
- 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
- 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!)
- 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.
- 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.
- 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
- 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
- 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
- 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
- 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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Steve Simon and was last modified on
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