Protecting Against Nonrandomly Missing Data in Longitudinal Studies

DOI10.2307/2531637zbMath0718.62215OpenAlexW2321237259WikidataQ30602734 ScholiaQ30602734MaRDI QIDQ5750242

C. Hendricks Brown

Publication date: 1990

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/2531637

zbMATH Keywords

incomplete datacensoringlongitudinal studiesNonrandomly missing dataprotective estimators

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) General nonlinear regression (62J02)

Related Items (14)

Bayesian latent pattern mixture models for handling attrition in panel studies with refreshment samples ⋮ Identifiability and Estimation of Causal Effects in Randomized Trials with Noncompliance and Completely Nonignorable Missing Data ⋮ Analysis of structural equation models with censored or truncated data via EM algorithm. ⋮ Log-linear models for a binary response with nonignorable nonresponse ⋮ Using the Fraction of Missing Information to Identify Auxiliary Variables for Imputation Procedures via Proxy Pattern‐mixture Models ⋮ A Brief Review of Approaches to Non‐ignorable Non‐response ⋮ Protective estimation of longitudinal categorical data with nonrandom dropout ⋮ Robust methods for generalized linear models with nonignorable missing covariates ⋮ Missing data mechanisms and their implications on the analysis of categorical data ⋮ An Index of Local Sensitivity to Nonignorability for a Pseudolikelihood Method ⋮ Analysis of incomplete longitudinal data with informative drop‐out and outliers ⋮ A pattern-mixture odds ratio model for incomplete categorical data ⋮ Robust analysis of longitudinal data with nonignorable missing responses ⋮ Protective estimator for linear regression with nonignorably missing Gaussian outcomes

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