Fitting multilevel multivariate models with missing data in responses and covariates that may include interactions and non-linear terms
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Publication:6651783
DOI10.1111/RSSA.12022WikidataQ58618844 ScholiaQ58618844MaRDI QIDQ6651783
Harvey Goldstein, William Browne, James Carpenter
Publication date: 11 December 2024
Published in: Journal of the Royal Statistical Society. Series A. Statistics in Society (Search for Journal in Brave)
endogeneitymissing datamultiple imputationMarkov chain Monte Carlo methodsmultilevel modellingmultivariate modellingmultiprocess modellatent normal model
Related Items (3)
Maximum Likelihood Estimation of Hierarchical Linear Models from Incomplete Data: Random Coefficients, Statistical Interactions, and Measurement Error ⋮ Recoverability and estimation of causal effects under typical multivariable missingness mechanisms ⋮ Substantive model compatible multilevel multiple imputation: a joint modeling approach
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