title: Fast and highly efficient pseudo-likelihood methodology for large and complex ordinal data.
abstract: In longitudinal studies, continuous, binary, categorical, and survival outcomes are often jointly collected, possibly with some observations missing. However, when it comes to modeling responses, the ordinal ones have received less attention in the literature. In a longitudinal or hierarchical context, the univariate proportional odds mixed model (POMM) can be regarded as an instance of the generalized linear mixed model (GLMM). When the response of the joint multivariate model encompass ordinal responses, the complexity further increases. An additional problem of model fitting is the size of the collected data. Pseudo-likelihood based methods for pairwise fitting, for partitioned samples and, as introduced in this paper, pairwise fitting within partitioned samples allow joint modeling of even larger numbers of responses. We show that that pseudo-likelihood methodology allows for highly efficient and fast inferences in high-dimensional large datasets.
authors.affiliation: 1 I-BioStat, KU Leuven, University of Leuven, Leuven, Belgium.
authors.forename: Anna
authors.initials: A
authors.lastname: Ivanova
authors.affiliation: 1 I-BioStat, KU Leuven, University of Leuven, Leuven, Belgium.|2 I-BioStat, Universiteit Hasselt, Hasselt, Belgium.
authors.forename: Geert
authors.initials: G
authors.lastname: Molenberghs
authors.affiliation: 1 I-BioStat, KU Leuven, University of Leuven, Leuven, Belgium.|2 I-BioStat, Universiteit Hasselt, Hasselt, Belgium.
authors.forename: Geert
authors.initials: G
authors.lastname: Verbeke
mesh_terms: D015415:Biomarkers / Q000097:blood; D056808:Biostatistics / Q000379:methods; D001794:Blood Pressure; D008078:Cholesterol, LDL / Q000097:blood; D003627:Data Interpretation, Statistical; D003920:Diabetes Mellitus / Q000097:blood / Q000503:physiopathology / Q000628:therapy; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D016013:Likelihood Functions; D016014:Linear Models; D008137:Longitudinal Studies; D015233:Models, Statistical; D013997:Time Factors
chemical_list: D015415:Biomarkers; D008078:Cholesterol, LDL; D006442:Glycated Hemoglobin; C517652:hemoglobin A1c protein, human
keywords: Generalized linear mixed model; asymptotic relative efficiency; joint modeling; pairwise fitting; proportional odds mixed model; pseudo-likelihood; reduced computation time; sample partition