Literature DB >> 27507289

A new parsimonious model for ordinal longitudinal data with application to subjective evaluations of a gastrointestinal disease.

Moreno Ursino1,2, Mauro Gasparini1.   

Abstract

In this paper, a new discrete statistical model for ordered categorical data is proposed via fixed-point discretization of a beta latent variable. The resulting discretized beta distribution has a highly flexible shape and it can be either over-dispersed or under-dispersed with respect to the binomial distribution. It has only two parameters, which may therefore parsimoniously depend on covariates and on random effects, providing new tools for the analysis of structured, clustered or longitudinal ordinal data. Practical examples and advices are given and an application of the new model to subjective evaluations of a gastrointestinal disease is shown.

Entities:  

Keywords:  Longitudinal data; beta distribution; mixed effect model; ordinal data; ordinal regression

Mesh:

Year:  2016        PMID: 27507289     DOI: 10.1177/0962280216661370

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  6 in total

1.  Modeling near-continuous clinical endpoint as categorical: application to longitudinal exposure-response modeling of Mayo scores for golimumab in patients with ulcerative colitis.

Authors:  Chuanpu Hu; Omoniyi J Adedokun; Liping Zhang; Amarnath Sharma; Honghui Zhou
Journal:  J Pharmacokinet Pharmacodyn       Date:  2018-10-30       Impact factor: 2.745

2.  Applying Beta Distribution in Analyzing Bounded Outcome Score Data.

Authors:  Chuanpu Hu; Honghui Zhou; Amarnath Sharma
Journal:  AAPS J       Date:  2020-03-17       Impact factor: 4.009

3.  Improving categorical endpoint longitudinal exposure-response modeling through the joint modeling with a related endpoint.

Authors:  Chuanpu Hu; Honghui Zhou
Journal:  J Pharmacokinet Pharmacodyn       Date:  2021-11-20       Impact factor: 2.745

4.  Two-part models for repeatedly measured ordinal data with "don't know" category.

Authors:  Ralitza Gueorguieva; Eugenia Buta; Meghan Morean; Suchitra Krishnan-Sarin
Journal:  Stat Med       Date:  2020-09-09       Impact factor: 2.373

5.  A phase I-II design based on periodic and continuous monitoring of disease status and the times to toxicity and death.

Authors:  Juhee Lee; Peter F Thall; Pavlos Msaouel
Journal:  Stat Med       Date:  2020-04-07       Impact factor: 2.497

6.  A Bounded Integer Model for Rating and Composite Scale Data.

Authors:  Gustaf J Wellhagen; Maria C Kjellsson; Mats O Karlsson
Journal:  AAPS J       Date:  2019-06-06       Impact factor: 4.009

  6 in total

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