Multiple imputation is illustrated for dealing with missing data in a published SCED study.
Results were compared to those obtained from available data. Merits and issues of …

Multiple Imputation in Practice: With Examples Using IVEware provides practical guidance
on multiple imputation analysis, from simple to complex problems using real and simulated …

Multiple Imputation of Missing Data in Practice: Basic Theory and Analysis Strategies
provides a comprehensive introduction to the multiple imputation approach to missing data …

Background Multiple imputation is becoming increasingly popular for handling missing data.
However, it is often implemented without adequate consideration of whether it offers any …

Aim To illustrate with the example of a secondary data analysis study the use of the multiple
imputation method to replace missing data. Background Most large public datasets have …

Background Sample loss and missing data are inevitable in multivariate and longitudinal
research. Ad hoc approaches such as analysis of incomplete data or substituting the group …

Multiple imputation: a primer - Joseph L Schafer, 1999 Skip to main content Intended for
healthcare professionals Sage Journals Home Search this journal Search all journals Enter …

It is now widely accepted that multiple imputation (MI) methods properly handle the
uncertainty of missing data over single imputation methods. Several standard statistical …

Educational researchers have become increasingly aware of the problems and biases
which can be caused by missing data. Significant advances have been made in the last 15 …

Within epidemiological and clinical research, missing data are a common issue which are
often inappropriately handled in practice. Multiple imputation (MI) is a popular tool used tofill …