Effectiveness of Valid Mean Substitution in Treating Missing Data in Attitude Assessment

Abstract

This study investigates the use of the valid mean substitution (VMS) procedure in replacing missing data in attitude assessment. Using four scales from an actual field data set, the effectiveness of VMS was compared with the multiple regression replacement procedure. The study was designed such that data were missing completely at random under two research conditions: percentage of missing items in each scale (10, 30 and 50%); percentage of missing values in each item (10, 30 and 50%). The results indicated that both procedures are similarly effective in estimating the means and standard deviations of the scales. However, VMS is superior in estimating parameters.