Behavioral science researchers routinely use scale scores that sum or average a set of
questionnaire items to address their substantive questions. A researcher applying multiple …

The performance of five simple multiple imputation methods for dealing with missing data
were compared. In addition, random imputation and multivariate normal imputation were …

This article compares a variety of imputation strategies for ordinal missing data on Likert
scale variables (number of categories= 2, 3, 5, or 7) in recovering reliability coefficients …

The last 20 years has seen an uptick in research on missing data problems, and most
software applications now implement one or more sophisticated missing data handling …

This article first discusses a statistical test for investigating whether or not the pattern of
missing scores in a respondent-by-item data matrix is random. Since this is an asymptotic …

Multiple imputation is a widely recommended means of addressing the problem of missing
data in psychological research. An often-neglected requirement of this approach is that the …

Researchers in many fields use multiple item scales to measure important variables such as
attitudes and personality traits, but find that some respondents failed to complete certain …

Multiple imputation is widely accepted as the method of choice to address item-nonresponse
in surveys. However, research on imputation strategies for the hierarchical structures that …

Multiple imputation is a popular technique used to handle item-level missing data. Recent
studies, however, have generated serious concerns about the best practices for statistical …

Analyses of multivariate data are frequently hampered by missing values. Until recently, the
only missing-data methods available to most data analysts have been relatively ad1 hoc …