The estimation and use of predictions for the assessment of model performance using large samples with multiply imputed data.

ABSTRACT: Multiple imputation can be used as a tool in the process of constructing prediction models in medical and epidemiological studies with missing covariate values. Such models can be used to make predictions for model performance assessment, but the task is made more complicated by the multiple imputation structure. We summarize various predictions constructed from covariates, including multiply imputed covariates, and either the set of imputation-specific prediction model coefficients or the pooled prediction model coefficients. We further describe approaches for using the predictions to assess model performance. We distinguish between ideal model performance and pragmatic model performance, where the former refers to the model's performance in an ideal clinical setting where all individuals

SUBMITTER: Wood AM 

PROVIDER: S-EPMC4515100 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature