To compensate for item nonresponse, hot deck imputation procedures replace missing values with values that occur in the sample. Fractional hot deck imputation replaces each missing observation with a set of imputed values and assigns a weight to each imputed value. Under the model in which observations in an imputation cell are independently and identically distributed, fractional hot deck impu...

We present three di erent methods based on the conditional mean im putation when binary explanatory variables are incomplete Apart from the single imputation and multiple imputation especially the so called pi imputation is presented as a new procedure Seven procedures are com pared in a simulation experiment when missing data are con ned to one independent binary variable complete case analysi...

This study compares imputation methods (single and multiple) to examine the role of perceived stress in the relationship between social support and mood, and tested whether mediator effects influenced the relationship. The cross-sectional data reported here was collected in an experimental design with repeated measures with mothers of children who had been hospitalized in a child psychiatric un...

Missing observations are common in cluster randomised trials. The problem is exacerbated when modelling bivariate outcomes jointly, as the proportion of complete cases is often considerably smaller than the proportion having either of the outcomes fully observed. Approaches taken to handling such missing data include the following: complete case analysis, single-level multiple imputation that i...

Objectives. Most researchers who use survey data must grapple with the problem of how best to handle missing information. This article illustrates multiple imputation, a technique for estimating missing values in a multivariate setting. Methods. I use multiple imputation to estimate missing income data and update a recent study that examines the influence of parents’ standard of living on subje...