Little's test of missing completely at random

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.


Issue Date:
2013
Publication Type:
Journal Article
DOI and Other Identifiers:
st0318 (Other)
PURL Identifier:
http://purl.umn.edu/252693
Published in:
Stata Journal, Volume 13, Number 4
Page range:
795-809
Total Pages:
17

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 Record created 2017-04-01, last modified 2017-04-28

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