Split-Plot Designs with Correlated Proportions
An extension of McNemar's test for correlated proportions was presented in which subjects falling into McNemar's A and D categories are nested under two or more levels of one or more between-subjects factors. The main effect for the within-subjects factor is tested with the McNemar chi-squared statistic used for correlated proportions after collapsing the one or more between-subjects factors. Two- and higher-way interactions between the one or more between-subjects factors and the correlated proportions factor are tested with the Pearson chi-squared statistic used for two- and higher-dimensional contingency tables, respectively, based on observations taken from independent samples.