Little's Test of Missing Completely at Random
Author:
- 1 December 2013
- journal article
- research article
- Published by SAGE Publications in The Stata Journal: Promoting communications on statistics and Stata
- Vol. 13 (4) , 795-809
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.Keywords
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