Many to one comparisons in a longitudinal binary data setup
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Motivated by an example we discuss the problem of comparison to control in a scenario where we have repeated binary data from a large number independent individuals under each comparison group. We use the generalized quasi-likelihood (GQL) estimators for the comparison group effects including the effect of the control group to define a single step and step-down method for performing many-to-one comparisons. We discuss the asymptotic properties of our method and provide ways of computing the critical values. We follow up with simulations for Type I error and marginal power and show that our proposed method performs well in practice.
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- Many to one comparisons in a longitudinal binary data setup
Volume 74, Issue 2 , pp 268-285
- Cover Date
- Print ISSN
- Online ISSN
- Additional Links
- Generalized quasi-likelihood
- comparison to control
- multivariate normal
- single step
- step down
- Type I error
- marginal power
- Primary 62J12
- Secondary 62F03