Hi, Esa!
You've had a couple of responses; here's another.
You state "pairwise comparisons"; but it strikes me as at least
possible that you might want (or might _also_ want) to consider more
complex comparisons if any such comparisons seemed to offer a more
parsimonious (or, perhaps, more theory-related?) explanation of the
differences among the four conditions. (E.g., conditions A & B vs.
conditions C & D; or, condition B vs. conditions A & C & D; or,
condition A vs. conditions B & D and condition C vs. conditions B & D.)
I would ordinarily think of using the Scheffe' method (or the
Tukey method, if the sample sizes were equal in each condition and one's
interest really were _only_ in pairwise comparisons): its experimentwise
Type I error rate means no need for Bonferroni or similar calculations;
just convert your binary response to a proportion passed (or proportion
failed, if that be easier to interpret) and do a one-way ANOVA on that
proportion in the four treatments.
-- Don.
On Fri, 2 Mar 2001, Esa M. Rantanen wrote:
> I have a question concerning pairwise comparisons between four
> treatment conditions. <snip> 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.
> ... Chi-Sq. analysis [has found] a statistically significant difference
> between the (treatment) groups (all 4!). <snip>
>
> I would appreciate [it] 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!
----------------------------------------------------------------------
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 (603) 535-2597
Department of Mathematics, Boston University [EMAIL PROTECTED]
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184 Nashua Road, Bedford, NH 03110 (603) 471-7128
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