mex provides a small toolbox for the researcher to explore their missing data. These tools consist of: t-tests and chi2, CART, BRT, clustering, and a missing data simulator. The t-test / chi2 tests compare whether the missingness is affecting the expected count or mean value. The CART (rpart) and BRT (gbm and gbm.step) functions explore the proportion of missing data in a row, and also interact with clustering (undecided method) of missingness. The data simulation function also makes it easy to create specific missingness patterns, as well as compare theorized missingness patterns found in your research.
|Author||Nicholas Tierney and Damjan Vukcevic|
|Maintainer||Nicholas Tierney <email@example.com> and Damjan Vukcevic <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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