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Little's test of missing completely at random

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  • Cheng Li

    (Northwestern University)

Abstract

In missing-data analysis, Little's test (1988, Journal of the American Statistical Association 83: 1198–1202) is useful for testing the assumption of missing completely at random for multivariate, partially observed quantitative data. I introduce the mcartest command, which implements Little's missing completely at random test and its extension for testing the covariate-dependent missingness. The command also includes an option to perform the likelihood-ratio test with adjustment for unequal variances. I illustrate the use of mcartest through an example and evaluate the finite-sample performance of these tests in simulation studies. Copyright 2013 by StataCorp LP.

Suggested Citation

  • Cheng Li, 2013. "Little's test of missing completely at random," Stata Journal, StataCorp LP, vol. 13(4), pages 795-809, December.
    • Handle: RePEc:tsj:stataj:v:13:y:2013:i:4:p:795-809
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