Social and Behavioral Sciences Commons^™

Analyzing Incomplete Categorical Data: Revisiting Maximum Likelihood Estimation (Mle) Procedure, Hoo Ling Ping, M. Ataharul Islam

Journal of Modern Applied Statistical Methods

Incomplete data poses formidable difficulties in the application of statistical techniques and requires special procedures to handle. The most common ways to solve this problem are by ignoring, truncating, censoring or collapsing those data, but these may lead to inappropriate conclusions because those data might contain important information. Most of the research for estimating cell probabilities involving incomplete categorical data is based on the EM algorithm. A likelihood approach is employed for estimating cell probabilities for missing values and makes comparisons between maximum likelihood estimation (MLE) and the EM algorithm. The MLE can provide almost the same estimates as that …