Generalized cochran-mantel-haenszel test statistics for correlated categorical data
- 1 January 1997
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 26 (8) , 1813-1837
- https://doi.org/10.1080/03610929708832016
Abstract
Three new test statistics are introduced for correlated categorical data in stratified R×C tables. They are similar in form to the standard generalized Cochran-Mantel-Haenszel statistics but modified to handle correlated outcomes. Two of these statistics are asymptotically valid in both many-strata (sparse data) and large-strata limiting models. The third one is designed specifically for the many-strata case but is valid even with a small number of strata. This latter statistic is also appropriate when strata are assumed to be random.Keywords
This publication has 18 references indexed in Scilit:
- Inference Based on Estimating Functions in the Presence of Nuisance ParametersStatistical Science, 1995
- A General Overview of Mantel-Haenszel Methods: Applications and Recent DevelopmentsAnnual Review of Public Health, 1988
- The Analysis of Cross-Classified Categorical Data from Complex Sample SurveysSociological Methodology, 1988
- The Power of the Mantel-Haenszel TestJournal of the American Statistical Association, 1987
- Small-Sample Comparisons of Level and Power for Simple Goodness-of-Fit Statistics Under Cluster SamplingJournal of the American Statistical Association, 1987
- Odds ratio inference with dependent dataBiometrika, 1985
- The Analysis of Categorical Data From Complex Sample Surveys: Chi-Squared Tests for Goodness of Fit and Independence in Two-Way TablesJournal of the American Statistical Association, 1981
- Analysis of contingency tables under cluster samplingBiometrika, 1980
- Approximate Tests of Independence and Goodness of Fit Based on Stratified Multistage SamplesJournal of the American Statistical Association, 1980
- Average Partial Association in Three-Way Contingency Tables: A Review and Discussion of Alternative TestsInternational Statistical Review, 1978