Hypothesis testing is a set of formal
methods to select between two competing research hypotheses. These pages discuss
some of the philosophical underpinnings for hypothesis testing as well as some
pragmatic concerns. Articles are arranged by date with the most recent entries
at the top. You can find outside resources
at the bottom of this page. Other entries about hypothesis testing can be found in the
Category:
Hypothesis testing page at the
StATS website.
2008
- P.Mean: What is an intervening
variable (created 2008-10-20). I'm familiar with dependent and
independent variables but I just heard about intervening variables. Please tell
me what are they, and how they deal with the other variables.
- Normality assumptions for the paired
t-test (created 2008-10-14). I am confused about which data have to be
normally distributed on a paired t-test for testing that two data sets differ
significantly. Everitt-Hothorn "A handbook of statistical analyses using R",
page 33 says that the differences between the data should be normally
distributed without implying anything about if the original data should be
normally distributed, while Wiki t-test and Field "Discovering statistics using
SPSS" page 287 imply that both of the original data should be normally
distributed? Considering that I am a beginner in statistics, I am confused. can
you give me any clues please?
- P.Mean: Comparing two proportions out of
the same multinomial population (created 2008-08-05). I am lucky enough
to be researching wine. Specifically I am exploring which components in wine
results in maximised preference. At the moment I am trying to compare
proportions from the same population. N = 68. 8 people most preferred wine 1, 25
most preferred wine 2, 1 most preferred wine 1 and 2, for 34 of participants
their most preferred wine was another wine. I want to see if the proportion of
people that chose wine 1 was significantly different from the proportion that
chose wine 2. I have been recommended to use McNemar's. But I just don't know
how. I found your website which is as close as I have got but is slightly
different. Just wondering if you had any thoughts? Cheers
- P.Mean: How to report a one-tailed Fisher's
Exact test (created 2008-07-12). Thank you for your informative page
about the Fisher's Exact test. Can you please clarify how whether the test was 1
or 2-tailed affects the way that a significant result would be reported?
Outside resources:
- An alternative to null-hypothesis significance
tests. P. R. Killeen. Psychol Sci 2005: 16(5); 345-53.
[Medline]
[Abstract]
[Full text]
[PDF]. Description: This article describes p-rep, a
statistic that measures the probability of replication. The article argues
that this measure is superior to the p-value and also covers the mathematical
details needed for calculation of the statistic.
-
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
-
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
- Luis Carlos Silva-Aycaguer, Patricio Suarez-Gil, Ana Fernandez-Somoano.
The null hypothesis significance test in health sciences research
(1995-2006): statistical analysis and interpretation. BMC Medical
Research Methodology. 2010;10(1):44. Abstract: "BACKGROUND: The null
hypothesis significance test (NHST) is the most frequently used statistical
method, although its inferential validity has been widely criticized since
its introduction. In 1988, the International Committee of Medical Journal
Editors (ICMJE) warned against sole reliance on NHST to substantiate study
conclusions and suggested supplementary use of confidence intervals (CI).
Our objective was to evaluate the extent and quality in the use of NHST and
CI, both in English and Spanish language biomedical publications between
1995 and 2006, taking into account the International Committee of Medical
Journal Editors recommendations, with particular focus on the accuracy of
the interpretation of statistical significance and the validity of
conclusions. METHODS: Original articles published in three English and three
Spanish biomedical journals in three fields (General Medicine, Clinical
Specialties and Epidemiology - Public Health) were considered for this
study. Papers published in 1995-1996, 2000-2001, and 2005-2006 were selected
through a systematic sampling method. After excluding the purely descriptive
and theoretical articles, analytic studies were evaluated for their use of
NHST with P-values and/or CI for interpretation of statistical
"significance" and "relevance" in study conclusions. RESULTS: Among 1,043
original papers, 874 were selected for detailed review. The exclusive use of
P-values was less frequent in English language publications as well as in
Public Health journals; overall such use decreased from 41 % in 1995-1996 to
21% in 2005-2006. While the use of CI increased over time, the "significance
fallacy" (to equate statistical and substantive significance) appeared very
often, mainly in journals devoted to clinical specialties (81%). In papers
originally written in English and Spanish, 15% and 10%, respectively,
mentioned statistical significance in their conclusions. CONCLUSIONS:
Overall, results of our review show some improvements in statistical
management of statistical results, but further efforts by scholars and
journal editors are clearly required to move the communication toward ICMJE
advices, especially in the clinical setting, which seems to be imperative
among publications in Spanish." [Accessed June 14, 2010]. Available at:
http://www.biomedcentral.com/1471-2288/10/44.
All of the material above this paragraph is licensed under a
Creative Commons Attribution 3.0 United States License. This page was written by
Steve Simon and was last modified on
2010-06-14. The material
below this paragraph links to my
old website, StATS. Although I wrote all of the material
listed below, my ex-employer, Children's Mercy Hospital, has claimed copyright
ownership of this material. The brief excerpts shown here are included under
the fair use provisions of U.S. Copyright laws.
2008
Stats: An alternative to the p-value
(April 3, 2008). A discussion on edstat-l concerned a statistic called
p-rep. I had not heard of this statistic before, but at least one journal is
calling for its use in all papers published by that journal.
Stats: What is a critical value?
(February 22, 2008). Someone wrote in asking about the difference between
a p-value and a critical value.
Stats: Type III
error (January 3, 2008). Dear Professor Mean, What is the
definition of a Type III error?
Stats: Further exploration
of Type I and Type II errors (April 5, 2007). I got some feedback that my
definitions of Type I errors and Type II errors would be clearer if I
specified what the actual hypothesis are. I wanted to avoid symbols like mu
or pi, so here is what I wrote.
Stats: Type II error (September 3, 1999).
Dear Professor Mean: A journal reviewer criticized the small sample size in
my research study and suggested that I mention a Type II error as a possible
explanation for my results. I've never heard this term before. What is a Type
II error?
Stats: T-test (April 18, 1999).
Dear Professor Mean: How do you analyze a t-test? I have a t-test value, and
I know that I have to compare it to a t-distribution. I'm not sure how to do
that.
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This work is licensed under a
Creative Commons Attribution 3.0 United States License. This page was written by
Steve Simon and was last modified on
2010-06-14.
