Missing data present a perennial challenge in scientific research, potentially undermining the validity of conclusions if not addressed rigorously. The analysis of missing data encompasses a broad ...

This is a preview. Log in through your library . Abstract A multiple-imputation method is developed for analysing data from an observational study where some covariate values are not observed. A ...

In recent years there has been considerable research devoted to the development of methods for the analysis of incomplete data in longitudinal studies. Despite these advances, the methods used in ...

Synchronous prostate and rectal cancers across a large distributed healthcare system: Implications for national accreditation program for rectal cancer (NAPRC) guidelines. This is an ASCO Meeting ...

Multiple imputation is a principled approach to account for missing data in analyses where valid results depends on careful construction of the imputation model. The potential for misspecification of ...

Missing data can plague researchers in many scenarios, arising from incomplete surveys, experimental objects broken or destroyed, or data collection/computational errors. This short course will ...

Missing data are almost inevitable in medical research. This leads to a loss of power and potential bias. Multiple imputation is a widely-used and flexible approach for handling missing data. This ...