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Title: Goodness-of-fit tests for correlated paired binary data
Authors: Tang, M.-L.
Pei, Y.-B.
Wong, W.-K.
Li, J.-L. 
Keywords: Akaike information criterion
bootstrap procedures
correlated binary data
model selection techniques
Rosner's and Dallal's models
Issue Date: Aug-2012
Citation: Tang, M.-L., Pei, Y.-B., Wong, W.-K., Li, J.-L. (2012-08). Goodness-of-fit tests for correlated paired binary data. Statistical Methods in Medical Research 21 (4) : 331-345. ScholarBank@NUS Repository.
Abstract: We review a few popular statistical models for correlated binary outcomes, present maximum likelihood estimates for the model parameters, and discuss model selection issues using a variety of goodness-of-fit test statistics. We apply bootstrap strategies that are computationally efficient to evaluate the performance of goodness-of-fit statistics and observe that generally the power and the type I error rate of the goodness-of-fit statistics depend on the model under investigation. Our simulation results show that careful choice of goodness-of-fit statistics is an important issue especially when we have a small sample and the outcomes are highly correlated. Two biomedical applications are included. © The Author(s) 2010 Reprints and permissions:
Source Title: Statistical Methods in Medical Research
ISSN: 09622802
DOI: 10.1177/0962280210381176
Appears in Collections:Staff Publications

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