Tests for paired count outcomes. Issue 1 (8th September 2018)

• Record Type: Journal Article
• Authors: Proudfoot, James A; Lin, Tuo; Wang, Bokai; Tu, Xin M
• Is Part Of: General psychiatry. Volume 31:Issue 1(2018)
• Publication Date: 2018-09-08
• Subjects: biostatistics -- statistics as topic -- epidemiologic methods -- investigative techniques -- analytical, diagnostic and therapeutic; Psychiatry -- Periodicals; 616.89
• DOI: 10.1136/gpsych-2018-100004
• Languages: English
• ISSNs: 2096-5923

Abstract

Abstract : For moderate to large sample sizes, all tests yielded pvalues close to the nominal, except when models were misspecified. The signed-rank test generally had the lowest power. Within the current context of count outcomes, the signed-rank test shows subpar power when compared with tests that are contrasted based on full data, such as the GEE. Parametric models for count outcomes such as the GLMM with a Poisson for marginal count outcomes are quite sensitive to departures from assumed parametric models. There is some small bias for all the asymptotic tests, that is, the signed-ranktest, GLMM and GEE, especially for small sample sizes. Resampling methods such as permutation can help alleviate this.