Analysis of long series of longitudinal ordinal data using marginalized models
type: Item
instance of: scholarly article
title: Analysis of long series of longitudinal ordinal data using marginalized models
zbMATH Open document ID: 1470.62017
author: Keunbaik Lee
author: Insuk Sohn
author: D. Kim
published in: Computational Statistics and Data Analysis
publication date: 2018-08-15T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62J12
Mathematics Subject Classification ID: 62M10
Mathematics Subject Classification ID: 62P10
zbMATH DE Number: 6918673
zbMATH Keywords: likelihood-based estimation
zbMATH Keywords: quasi-Newton
zbMATH Keywords: quality of life
MaRDI profile type: Publication
full work available at URL: j.csda.2015.07.010
OpenAlex ID: W1104094100
cites work: A new look at the statistical model identification
cites work: Approximate Inference in Generalized Linear Mixed Models
cites work: Trend in correlated proportions
cites work: Random Effects Probit and Logistic Regression Models for Three-Level Data
cites work: Q4430630
cites work: Marginally Specified Logistic‐Normal Models for Longitudinal Binary Data
cites work: Marginalized Transition Models and Likelihood Inference for Longitudinal Categorical Data
cites work: Linear and Generalized Linear Models and their Applications by J. JIANG
cites work: Likelihood-based approach for analysis of longitudinal nominal data using marginalized random effects models
cites work: Analysis of zero-inflated clustered count data: a marginalized model approach
cites work: Longitudinal nominal data analysis using marginalized models
cites work: Marginalized Models for Moderate to Long Series of Longitudinal Binary Response Data
cites work: Q3221234
DOI: 10.1016/J.CSDA.2015.07.010
description: scientific article; zbMATH DE number 6918673