title: Population-averaged and cluster-specific models for clustered ordinal response data.
abstract: We compare population-averaged and cluster-specific models for clustered ordinal data. We consider generalized estimating equations and constrained equations maximum likelihood estimation of population-averaged cumulative logit regression models, and mixed effects estimation of cluster-specific cumulative logit regression models. A previously reported relationship between population-averaged and cluster-specific parameters for the binary logistic link appears to hold for analogous parameters under the cumulative logit link. We address these issues in the context of data from two cross-over clinical trials.
authors.affiliation: Center for Biostatistics and Epidemiology, Hershey Medical Center, Pennsylvania State University, Hershey 17033, USA.
authors.forename: T R
authors.initials: TR
authors.lastname: Ten Have
authors.forename: J R
authors.initials: JR
authors.lastname: Landis
authors.forename: J
authors.initials: J
authors.lastname: Hartzel
mesh_terms: D016009:Chi-Square Distribution; D002986:Clinical Trials as Topic / Q000379:methods*; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D003710:Demography; D004412:Dysmenorrhea / Q000188:drug therapy; D005260:Female; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D016015:Logistic Models; D015233:Models, Statistical; D009330:Nebulizers and Vaporizers / Q000145:classification; D013029:Space-Time Clustering