Multivariate analysis of variance (MANOVA) is widely used in educational research to
compare means on multiple dependent variables across groups. Researchers faced with the …

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 …

Missing data is endemic in much educational research. However, practices such as step-
wise regression common in the educational research literature have been shown to be …

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 …

Multilevel data are often incomplete, for example, when participants refuse to answer some
items in a questionnaire or drop out of a study that involves multiple measurement …

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 …

Multiple imputation is an increasingly popular strategy for analyzing data with missing
values (Allison, 2002; Rubin, 1987). In multiple imputation, the analyst creates several …

St. John's University n the Orsak, Mendro, and Weerasinghe article (pp. 3-12), the authors
search for an acceptable methodology for estimating missing student post-test scores within …

Statistical analysis with missing data has always been a challenge. However, there have
been tremendous advances in statistical theory related to analysis with missing data. Of …

Higher education researchers using survey data often face decisions about handling
missing data. Multiple imputation (MI) is considered by many statisticians to be the most …