Missing Exposure Data in Stereotype Regression Model: Application to Matched Case-Control Study with Disease Subclassification

DOI10.1111/j.1541-0420.2010.01453.xzbMath1217.62159OpenAlexW2112921023WikidataQ33609090 ScholiaQ33609090MaRDI QIDQ3013984

Stephen B. Gruber, Bhramar Mukherjee, Jaeil Ahn, Samiran Sinha

Publication date: 19 July 2011

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc3119773

zbMATH Keywords

conditional likelihoodproportional oddsnonignorable missingnessstages of cancervector generalized linear model

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15) Generalized linear models (logistic models) (62J12) Monte Carlo methods (65C05) Medical applications (general) (92C50) Estimation in survival analysis and censored data (62N02)

Related Items (3)

Assigning scores for ordered categorical responses ⋮ A latent class model to multiply impute missing treatment indicators in observational studies when inferences of the treatment effect are made using propensity score matching ⋮ Handling missing data in matched case‐control studies using multiple imputation

Uses Software

• CODA
• VGAM

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• On the estimation of the stereotype regression model
• A note on bias due to fitting prospective multivariate generalized linear models to categorical outcomes ignoring retrospective sampling schemes
• Inference from iterative simulation using multiple sequences
• Maximum likelihood estimation via the ECM algorithm: A general framework
• Reduced-rank vector generalized linear models
• Bayesian Semiparametric Modeling for Matched Case–Control Studies with Multiple Disease States
• Nonignorable Missingness in Matched Case-Control Data Analyses
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
• The Calculation of Posterior Distributions by Data Augmentation
• Fitting regression models to case-control data by maximum likelihood
• Adaptive Rejection Metropolis Sampling within Gibbs Sampling
• Semiparametric inference in matched case-control studies with missing covariate data
• Conditional and Unconditional Categorical Regression Models with Missing Covariates
• Likelihood Methods for Missing Covariate Data in Highly Stratified Studies
• Inferences About Exposure-Disease Associations Using Probability-of- Exposure Information
• A Comparison of Regression Models for the Analysis of Ordered Categorical Data
• Adaptive Rejection Sampling for Gibbs Sampling
• Matched Case–Control Data Analyses with Missing Covariates
• A review of ordinal regression models applied on health-related quality of life assessments
• Analysis of Matched Case–Control Data in Presence of Nonignorable Missing Exposure
• Equivalence Between Conditional and Mixture Approaches to the Rasch Model and Matched Case-Control Studies, With Applications
• Semiparametric Bayesian Analysis of Matched Case-Control Studies With Missing Exposure
• Cumulative Frequency Functions

This page was built for publication: Missing Exposure Data in Stereotype Regression Model: Application to Matched Case-Control Study with Disease Subclassification