Tests for homogeneity of the risk difference when data are sparse
Related Experiment Video
Updated: Oct 30, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
S R Lipsitz1, K B Dear, N M Laird
1Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. lipsitz@biostat.harvard.edu
Abstract:
Test statistics for the homogeneity of the risk difference for a series of 2 x 2 tables when the data are sparse is proposed. A weighted least squares statistic is commonly used to test for equality of the risk difference over the tables; however, when the data are sparse, this statistic can have anticonservative Type I error rates. Simulation is used to compare the proposed test statistics to the weighted least squares statistic. The weighted least squares statistic has the most anticonservative Type I error rates of all the statistics compared. We suggest the use of one of our proposed test statistics instead of the weighted least squares statistic.
Related Concept Videos
Test for Homogeneity
Comparing the Survival Analysis of Two or More Groups
One-Way ANOVA: Unequal Sample Sizes
Kruskal-Wallis Test
Bonferroni Test
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
One-Way ANOVA: Equal Sample Sizes
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
