Longitudinal data are not uncommon in many disciplines where repeated measurements on a response variable are collected for all subjects. Some intended measurements may not be available for some subjects resulting in a missing data pattern. Dropout pattern occurs when some subjects leave the study prematurely. The missing data pattern is defined as intermittent if a missing value followed by an...

One of the important stages of data mining is preprocessing, where the data is prepared for different mining tasks. Often, the real-world data tends to be incomplete, noisy, and inconsistent. It is very common that the data are not obtainable for every observation of every variable. So the presence of missing variables is obvious in the data set. A most important task when preprocessing the dat...

We appreciate the comments from the associate editor and all reviewers in this paper. We have made necessary experiments and modifications to cope with all the comments. The basic notations for different fonts are: Bold face fonts are from reviewers' original comments. Italic face fonts are the modified/added texts in the paper. Plain fonts are our answers to reviewers' comments. Q1: There is a...