Monte carlo EM for missing covariates in parametric regression models

Biometrics

Volumn 55, Issue 2, 1999, Pages 591-596

  Ibrahim, Joseph G ^a   Chen, Ming Hui ^b   Lipsitz, Stuart R ^a  

^a DANA FARBER CANCER INSTITUTE   (United States)

^b Worcester Polytechnic Institute   (United States)

Author keywords

EM algorithm; Generalized linear model; Gibbs sampler; Maximum likelihood estimation; Missing data mechanism; Poisson regression; Proportional hazards; Weibull regression

Indexed keywords

MONTE CARLO METHODS; PARAMETER ESTIMATION; REGRESSION ANALYSIS;

EM ALGORITHMS; GENERALIZED LINEAR MODEL; GIBBS SAMPLERS; MAXIMUM-LIKELIHOOD ESTIMATION; MISSING DATA; MISSING DATA MECHANISM; POISSON REGRESSION; PROPORTIONAL HAZARDS; WEIBULL; WEIBULL REGRESSION;

MAXIMUM LIKELIHOOD ESTIMATION;

ALGORITHM; ARTICLE; COVARIANCE; DATA ANALYSIS; HUMAN; LINEAR SYSTEM; LIVER CANCER; MATHEMATICAL COMPUTING; MAXIMUM LIKELIHOOD METHOD; REGRESSION ANALYSIS; STATISTICAL MODEL; STATISTICS; SYSTEM ANALYSIS;

EID: 0032969451     PISSN: 0006341X     EISSN: None     Source Type: Journal    
DOI: 10.1111/j.0006-341X.1999.00591.x     Document Type: Article

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