title: Tests for homogeneity of the risk difference when data are sparse.
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.
authors.affiliation: Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. lipsitz@biostat.harvard.edu
authors.forename: S R
authors.initials: SR
authors.lastname: Lipsitz
authors.forename: K B
authors.initials: KB
authors.lastname: Dear
authors.forename: N M
authors.initials: NM
authors.lastname: Laird
authors.forename: G
authors.initials: G
authors.lastname: Molenberghs
mesh_terms: D000970:Antineoplastic Agents / Q000627:therapeutic use; D001699:Biometry / Q000379:methods*; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D016018:Least-Squares Analysis; D009369:Neoplasms / Q000188:drug therapy; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012306:Risk
chemical_list: D000970:Antineoplastic Agents