Performing likelihood ratio tests with multiply-imputed data sets
From MaRDI portal
Publication:4020600
DOI10.1093/biomet/79.1.103zbMath0754.62041OpenAlexW2046205654MaRDI QIDQ4020600
Publication date: 17 January 1993
Published in: Biometrika (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1093/biomet/79.1.103
\(p\)-valuessignificance levelsWald test statisticvariance-covariance matricescomplete-data log likelihood ratio based procedurelog likelihood ratio test statisticsmultiparameter incomplete-data problemsmultiply-imputed data
Related Items (16)
General and feasible tests with multiply-imputed datasets ⋮ Multiple Imputation Methods for Multivariate One-Sided Tests with Missing Data ⋮ Conceptual, computational and inferential benefits of the missing data perspective in applied and theoretical statistical problems ⋮ Multiple Improvements of Multiple Imputation Likelihood Ratio Tests ⋮ Identifying individual predictive factors for treatment efficacy ⋮ Missing data: A statistical framework for practice ⋮ Inferences for two-stage multiple imputation for nonresponse ⋮ Order selection tests with multiply imputed data ⋮ Tests of independence in incomplete multi-way tables using likelihood functions ⋮ Imputation and Variable Selection in Linear Regression Models with Missing Covariates ⋮ Significance tests for multi-component estimands from multiply imputed, synthetic microdata ⋮ Likelihood‐based Inference with Missing Data Under Missing‐at‐Random ⋮ Missing covariates in logistic regression, estimation and distribution selection ⋮ Computational methods to simultaneously compare the predictive values of two diagnostic tests with missing data: EM-SEM algorithms and multiple imputation ⋮ Comparison of methods for incomplete repeated measures data analysis in small samples ⋮ Handling attrition in longitudinal studies: the case for refreshment samples
This page was built for publication: Performing likelihood ratio tests with multiply-imputed data sets
