On testing proportional odds assumptions for proportional odds models  

作　　者：Anqi Liu Hua He Xin M Tu Wan Tang 

机构地区：[1]Department of Bostaistis and Data Science,Tulane University,New Orleans,Louisiana,USA [2]Department of Epidemiology,Tulane University,New Orleans,Louisiana,USA [3]Division of Biostatistics and Bioinformatics,Herbert Wertheim School of Public Health and Human Longevity Science,UC San Diego,La Jolla,California,USA

出　　处：《General Psychiatry》2023年第3期214-219,共6页综合精神医学（英文）

基　　金：supported by the National Institutes of Health(NIH)(grant UL1TR001442)。

摘　　要：Proportional odds models are commonly used to model ordinal responses,but the proportional odds assumption may not hold in practice,leading to biased inference.Tests such as score,Wald and likelihood ratio(LR)have been proposed to evaluate the proportional odds assumption based on models without the assumption.Brant has proposed an independent binary model-based Wald-type test,and Wolfe and Gould have extended the idea to propose an LR-type test.This paper provides a brief review of the Brant and Wolfe-Gould tests for evaluating the proportional odds assumption and evaluates their performance through simulation studies and a real data example.Sample programs are provided in SAS,SPSS and Stata to facilitate the implementation of these tests using standard statistical software packages.This study highlights the importance of evaluating the proportional odds assumption when using proportional odds models for ordinal responses.The sample programs provided in this paper make it easy for researchers to apply these tests in their own analyses using standard statistical software packages.

关 键 词：GOULD TESTING apply 

分 类 号：R749[医药卫生—神经病学与精神病学]