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Biometrics. 1993 Dec;49(4):997-1009.

Marginal modeling of binary cross-over data.

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  • 1Department of Biostatistics, University of Michigan, Ann Arbor 48109-2029.


A model specified in terms of linear models for marginal logits and linear models for log-odds ratios is proposed for the analysis of two-period binary cross-over experiments. Hypothesis testing and parameter estimation are facilitated by standard likelihood methodology. Two examples are used to illustrate how the model can be used to analyze two-period binary cross-over experiments. Results from a simulation study demonstrate that this approach to the analysis of binary cross-over data compares favorably with standard procedures, such as the Mainland-Gart test for a treatment difference, Prescott's test for a treatment difference, and the Hills-Armitage test for treatment-by-period interaction.

[PubMed - indexed for MEDLINE]
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