A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates
type: Item
instance of: scholarly article
title: A computationally efficient method for nonlinear mixed-effects models with nonignorable missing data in time-varying covariates
zbMATH Open document ID: 1161.62381
author: Lang Wu
published in: Computational Statistics and Data Analysis
publication date: 2009-05-29T00:00:00Z
Mathematics Subject Classification ID: 62J02
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 65C60
zbMATH DE Number: 5559415
zbMATH Keywords: EM algorithm
zbMATH Keywords: linearization
zbMATH Keywords: longitudinal data
zbMATH Keywords: random effects model
MaRDI profile type: Publication
full work available at URL: j.csda.2006.07.036
OpenAlex ID: W2012273085
cites work: Convergence of the Monte Carlo expectation maximization for curved exponential families.
cites work: Sampling-Based Approaches to Calculating Marginal Densities
cites work: Adaptive Rejection Sampling for Gibbs Sampling
cites work: Random-Effects Models for Longitudinal Data
cites work: Q3949804
cites work: Nonparametric Mixed Effects Models for Unequally Sampled Noisy Curves
cites work: A Random-Effects Model for Multiple Characteristics With Possibly Missing Data
cites work: Q4342048
cites work: Conditional Second-Order Generalized Estimating Equations for Generalized Linear and Nonlinear Mixed-Effects Models
cites work: Nonlinear mixed-effect models with nonignorably missing covariates
cites work: Exact and Approximate Inferences for Nonlinear Mixed-Effects Models With Missing Covariates
cites work: Missing Time-Dependent Covariates in Human Immunodeficiency Virus Dynamic Models
DOI: 10.1016/J.CSDA.2006.07.036
description: scientific article; zbMATH DE number 5559415