It sounds to me like are are dealing with a comparison of four
proportions... Why can't you follow up the initial test with the six
pairwise tests of proportions, using some type of Bonferroni
correction... There's the Holm modification and the FDR procedure, both of
which give adequate protection with greater power than a "pure" Bonferroni
approach...
WBW
__________________________________________________________________________
William B. Ware, Professor and Chair Educational Psychology,
CB# 3500 Measurement, and Evaluation
University of North Carolina PHONE (919)-962-7848
Chapel Hill, NC 27599-3500 FAX: (919)-962-1533
http://www.unc.edu/~wbware/ EMAIL: [EMAIL PROTECTED]
__________________________________________________________________________
On Fri, 2 Mar 2001, Esa M. Rantanen wrote:
> Dear All:
>
> I have a question concerning pairwise comparisons between four treatment
> conditions. My experience is mostly with ANOVA, and (I think!) I can
> understand the reasoning for the use of multiple comparison procedures
> (e.g., Duncan's, Tukey's, or LSD) instead of individual t-tests between
> conditions.
>
> I assume the case is the same with my current problem: I have a single
> -factor experiment with four levels of the factor (treatment conditions)
> and a discrete dependent measure (pass/fail), resulting in a 2 x 4
> contingency table. I have used a Chi-Sq. analysis to determine if there is
> a statisitcally significant difference between the (treatment) groups (all
> 4!), and indeed there is. I assume, however, that I cannot simply do
> pairwise comparisons between the groups using Chi-Sq. and 2 x 2 matrices
> without inflating the probability of Type 1 error, (1-alpha)^4 in this
> case. As far as I know, there are no equivalents to Duncan's or Tukey's
> tests for the type of data (binary) I have to deal with.
>
> I would appreciate if anyone would confirm my reasoning above and offer any
> advice on how to proceed with the analysis of pairwise differences in the
> case of categorical (dichotomous) data. References to relevant literature
> would also be welcome!
>
> Best,
>
> Esa
> ____________________________
> Esa M. Rantanen, Ph.D.
> Assistant Professor
> University of Illinois at Urbana-Champaign
> Institute of Aviation, Aviation Human Factors Division
> Aviation Research Laboratory, Q5, MC-394
> One Airport Road, Willard Airport
> Savoy, IL 61874
> Tel. 217-244-8657 (ARL)
> Tel. 217-244-7397 (Psych.)
> Tel. 217-373-8276 (Home)
> Fax 217-244-8647
> e-mail: [EMAIL PROTECTED]
> url: http://www.aviation.uiuc.edu
> ____________________________
>
>
>
>
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