In the modern world information has become the new power. An increasing amount of efforts are being made to gather data, resources being allocated, time being invested and tools being developed. Data collection is no longer a myth; however, it remains a great challenge to create value out of the enormous data that is being collected. Data modeling…

Many methods exist for imputing missing data but fewer methods have been proposed to test the missing data mechanism. Little (1988) introduced a multivariate chi-square test for the missing completely at random data mechanism (MCAR) that compares observed means for each pattern with expectation-maximization (EM) estimated means. As an alternative,…

This study looked at the effect of a number of factors such as the choice of analytical method, the handling method for missing data, sample size, and proportion of missing data, in order to evaluate the effect of missing data treatment on accuracy of estimation. In order to accomplish this a methodological approach involving simulated data was…