title: Parametric robust inferences for correlated ordinal data.
abstract: The aim of this article is to provide asymptotically valid likelihood inferences about regression parameters for correlated ordinal response variables. The legitimacy of this novel approach requires no knowledge of the underlying joint distributions so long as their second moments exist. The efficacy of the proposed parametric approach is demonstrated via simulations and the analyses of two real data sets.
authors.affiliation: Institute of Statistics, National Central University, Taiwan, Province of China. tsou@mx.stat.ncu.edu.tw
authors.forename: Tsung-Shan
authors.initials: TS
authors.lastname: Tsou
authors.forename: Chung-Wei
authors.initials: CW
authors.lastname: Shen
mesh_terms: D000465:Algorithms; D032761:Animal Experimentation / Q000706:statistics & numerical data; D000818:Animals; D035843:Biomedical Research / Q000706:statistics & numerical data*; D016013:Likelihood Functions; D016014:Linear Models; D016016:Proportional Hazards Models; D016896:Treatment Outcome