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RE: st: Post Hoc Cross Tabulation Tests

From   Cameron McIntosh <>
Subject   RE: st: Post Hoc Cross Tabulation Tests
Date   Wed, 4 Jan 2012 19:54:10 -0500


Take a look at:

MacDonald, P.L., & Gardner, R.C. (2000). Type I Error Rate Comparisons of Post Hoc Procedures for I j Chi-Square Tables. Educational and Psychological Measurement, 60(5), 735-754.

García-Pérez, M.A., & Núñez-Antón, V. (2003). Cellwise Residual Analysis in Two-Way Contingency Tables. Educational and Psychological Measurement, 63(5), 825-839.

Cox, M.K., & Key, C.H. (1993). Post Hoc Pair-Wise Comparisons for the Chi-Square Test of Homogeneity of Proportions. Educational and Psychological Measurement, 53(4), 951-962.

Seaman, M.A., & Hill, C.C. (1996). Pairwise Comparisons for Proportions: A Note on Cox and Key. Educational and Psychological Measurement, 56(3), 452-459.

> Date: Wed, 4 Jan 2012 18:42:00 -0500
> Subject: st: Post Hoc Cross Tabulation Tests
> From:
> To:
> I am running an analysis examining the difference in prevalence for
> dichotomous (yes/no) substance abuse variables across a nominal
> variable with 5 categories in a nationally representative dataset.
> My goal is to identify significant differences overall and to identify
> significant differences between nominal categories (e.g. substance
> abuse rates are significantly different between White and African
> American youth, but not African American and Hispanic). If my
> substance abuse variables were continuous then I would use an ANOVA
> and use multiple comparison tests to identify category differences
> with syntax like:
> “oneway dv iv, t bon sid sch”
> Currently, however, I am using the following syntax to test for
> overall differences:
> “svy: tab substance iv, column ci per”
> That gives me point estimates, confidence intervals, chi2, and an F
> statistic. All of these are helpful, but is there a simple way that I
> can do the equivalent of the post hoc ANOVA comparison tests with my
> cross- tabulation? Or is there another way of testing overall
> difference and individual category differences using my dichotomous
> and nominal variables?
> *
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