Analyzing incomplete discrete longitudinal clinical trial data

DOI10.1214/088342305000000322zbMath1426.62316arXivmath/0606497OpenAlexW2081983881MaRDI QIDQ2381764

Ivy Jansen, Craig Mallinckrodt, Geert Verbeke, Caroline Beunckens, Geert Molenberghs

Publication date: 18 September 2007

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/math/0606497

zbMATH Keywords

sensitivity analysisgeneralized estimating equationsmissing at randomgeneralized linear mixed modelsignorabilitymissing completely at randomlast observation carried forwardmissing not at randomcomplete case analysis

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Generalized linear models (logistic models) (62J12)

Related Items (11)

Formal and informal model selection with incomplete data ⋮ Likelihood inference for models with unobservables: another view ⋮ Different methods for handling incomplete longitudinal binary outcome due to missing at random dropout ⋮ The nature of sensitivity in monotone missing not at random models ⋮ Repeated measures proportional odds logistic regression analysis of ordinal score data in the statistical software package R ⋮ A Latent‐Class Mixture Model for Incomplete Longitudinal Gaussian Data ⋮ Strategies for handling missing data in longitudinal studies with questionnaires ⋮ Longitudinal conditional models with intermittent missingness: SAS code and applications ⋮ A Bayesian transition model for missing longitudinal binary outcomes and an application to a smoking cessation study ⋮ A simulation study comparing weighted estimating equations with multiple imputation based estimating equations for longitudinal binary data ⋮ Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure

Uses Software

• Fahrmeir

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Longitudinal data analysis using generalized linear models
• Fahrmeir
• Likelihood based frequentist inference when data are missing at random
• Unified methods for censored longitudinal data and causality
• Models for discrete longitudinal data.
• A Local Influence Approach Applied to Binary Data from a Psychiatric Study
• Inference and missing data
• Model-based Inference for Categorical Survey Data Subject to Non-ignorable Non-response
• A comparison of the random-effects pattern mixture model with last-observation-carried-forward(locf) analysis in longitudinal clinical trials with dropouts
• A note on the comparison of pseudo-likelihood and generalized estimating equations for marginally specified odds ratio models with exchangeable association structure
• Simultaneously Modeling Joint and Marginal Distributions of Multivariate Categorical Responses
• Marginal Modeling of Correlated Ordinal Data Using a Multivariate Plackett Distribution
• Conditional Log-Linear Models for Analyzing Categorical Panel Data
• Frequentist Model Average Estimators
• Semiparametric Regression for Repeated Outcomes with Nonignorable Nonresponse
• Approximate Inference in Generalized Linear Mixed Models
• Assessing Response Profiles from Incomplete Longitudinal Clinical Trial Data Under Regulatory Considerations
• Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
• Logistic Regression for Correlated Binary Data
• Generalized linear mixed models a pseudo-likelihood approach
• A Saturated Model for Analyzing Exchangeable Binary Data: Applications to Clinical and Developmental Toxicity Studies
• Analyzing incomplete longitudinal clinical trial data
• NOTE ON AN EXACT TREATMENT OF CONTINGENCY, GOODNESS OF FIT AND OTHER PROBLEMS OF SIGNIFICANCE
• Linear mixed models for longitudinal data
• Multivariate statistical modelling based on generalized linear models.

This page was built for publication: Analyzing incomplete discrete longitudinal clinical trial data