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Sensitivity analysis of incomplete longitudinal data departing from the missing at random assumption: Methodology and application in a clinical trial with drop-outs.Selection models and pattern-mixture models for incomplete data with covariates.Analysing longitudinal continuous quality of life data with dropout.The impact of missing data on the results of a schizophrenia study.A Flexible Bayesian Approach to Monotone Missing Data in Longitudinal Studies with Nonignorable Missingness with Application to an Acute Schizophrenia Clinical Trial.Bayesian analysis of hierarchical pattern-mixture models for clinical trials data with attrition and comparisons to commonly used ad-hoc and model-based approaches.Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation MethodsIncomplete hierarchical data.Selection models and pattern-mixture models to analyse longitudinal quality of life data subject to drop-out.Sensitivity analysis of informatively coarsened data using pattern mixture models.A note on MAR, identifying restrictions, model comparison, and sensitivity analysis in pattern mixture models with and without covariates for incomplete data.A marginalized conditional linear model for longitudinal binary data when informative dropout occurs in continuous time.A characterization of missingness at random in a generalized shared-parameter joint modeling framework for longitudinal and time-to-event data, and sensitivity analysis.Implementation of pattern-mixture models in randomized clinical trials.Analysis of longitudinal trials with protocol deviation: a framework for relevant, accessible assumptions, and inference via multiple imputation.Last observation carried forward: a crystal ball?Quantile regression in the presence of monotone missingness with sensitivity analysis.A pattern-mixture model with nonfuture dependence and shift in current missing values.A pattern-mixture model for longitudinal binary responses with nonignorable nonresponse.Bayesian methods for nonignorable dropout in joint models in smoking cessation studies.On the joint analysis of longitudinal responses and early discontinuation in randomized trials.Jointly modelling the relationship between survival and pulmonary function in cystic fibrosis patients.Generalized shared-parameter models and missingness at randomReparameterizing the Pattern Mixture Model for Sensitivity Analyses Under Informative Dropout
P2860
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P2860
description
article
@en
wetenschappelijk artikel
@nl
наукова стаття, опублікована в червні 1998
@uk
name
Monotone missing data and pattern-mixture models
@en
Monotone missing data and pattern-mixture models
@nl
type
label
Monotone missing data and pattern-mixture models
@en
Monotone missing data and pattern-mixture models
@nl
prefLabel
Monotone missing data and pattern-mixture models
@en
Monotone missing data and pattern-mixture models
@nl
P2093
P356
P1476
Monotone missing data and pattern-mixture models
@en
P2093
B. Michiels
G. Molenberghs
M. G. Kenward
P. J. Diggle
P304
P356
10.1111/1467-9574.00075
P577
1998-06-01T00:00:00Z