Marginal modeling of binary cross-over data.

M P Becker; C C Balagtas

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PubMed · 8117910

Marginal modeling of binary cross-over data.

M P Becker·C C Balagtas

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Abstract

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.

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Biometry Cerebrovascular Disorders Clinical Trials as Topic Computer Simulation Data Interpretation, Statistical Humans Linear Models Logistic Models Models, Statistical Odds Ratio Software Journal Article Research Support, U.S. Gov't, P.H.S.

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M P Becker, C C Balagtas. 1993. Marginal modeling of binary cross-over data.. https://pubmed.ncbi.nlm.nih.gov/8117910/

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