%0 Journal Article
%T Missing data exploration: highlighting graphical presentation of missing pattern
%A Zhongheng Zhang
%J SCIE-indexed Journal
%D 2015
%R 10.3978/j.issn.2305-5839.2015.12.28
%X The previous article of big-data clinical trial series has introduced basic techniques in dealing with missing values. There are several R packages that allow advanced methods for managing missing data. Some useful methods include visual presentation of missing data pattern and correlation analysis (1). This article firstly creates a dataset containing five variables. Three missing data classes are illustrated in creating the dataset by simulation. Then various tools for the exploration of missing data are introduced
%U http://atm.amegroups.com/article/view/8666/9333