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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/387

Title: An exact trend test for correlated binary data
Authors: Corcoran, Christopher
Ryan, Louise
Mehta, Cyrus
Senchaudhuri, Pralay
Patel, Nitin
Molenberghs, Geert
Keywords: Non and semiparametric methods
Clustered data
Categorical data
Issue Date: 2001
Citation: Biometrics, 57(3). p. 941-948
Abstract: The problem of testing a dose-response relationship in the presence of exchangeably correlated binary data has been addressed using a variety of models. Most commonly used approaches are derived from likelihood or generalized estimating equations and rely on large-sample theory to justify their inferences. However, while earlier work has determined that these methods may perform poorly for small or sparse samples, there are few alternatives available to those faced with such data. We propose an exact trend test for exchangeably correlated binary data when groups of correlated observations are ordered. This exact approach is based on an exponential model derived by Molenberghs and Ryan (1999) and Ryan and Molenberghs (1999) and provides natural analogues to Fisher's exact test and the binomial trend test when the data are correlated. We use a graphical method with which one can efficiently compute the exact tail distribution and apply the test to two examples.
URI: http://hdl.handle.net/1942/387
DOI: 10.1111/j.0006-341X.2001.00941.x
ISI #: 000170732400036
ISSN: 0006-341X
Category: A1
Type: Journal Contribution
Validation: ecoom, 2002
Appears in Collections: Research publications

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