Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure-Reference-Cited by-同舟云学术

Handling non-ignorable dropouts in longitudinal data: a conditional model based on a latent Markov heterogeneity structure

Published:2014-08-24 Issue:1 Volume:24 Page:84-109
ISSN:1133-0686
Container-title:TEST
language:en
Short-container-title:TEST

Author:

Maruotti Antonello

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

http://link.springer.com/content/pdf/10.1007/s11749-014-0397-z.pdf

Reference42 articles.

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3. Alfò M, Aitkin M (2000) Random coefficient models for binary longitudinal responses with attrition. Stat Comput 10:279–287

4. Alfò M, Maruotti A (2009) A selection model for longitudinal binary responses subject to non-ignorable attrition. Stat Med 28:2435–2450

5. Bacci S, Pandolfi A, Pennoni F (2014) A comparison of some criteria for states selection in the latent Markov model for longitudinal data. Adv Data Anal Classif 8:125–145

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