Sample size and power calculations with correlated binary data

Controlled Clinical Trials

Volumn 22, Issue 3, 2001, Pages 211-227

  Pan, Wei ^a,b  

^a UNIVERSITY OF MINNESOTA   (United States)

^b Division of Biostatistics   (United States)

Author keywords

Clinical trials; GEE; Logistic regression; Sandwich estimator; Z test

Indexed keywords

ARTICLE; CLINICAL TRIAL; CLUSTER ANALYSIS; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; REGRESSION ANALYSIS; SAMPLE; STATISTICAL ANALYSIS; STATISTICAL MODEL; VARIANCE;

CLINICAL TRIALS; HUMANS; LOGISTIC MODELS; SAMPLE SIZE;

EID: 0034992722     PISSN: 01972456     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0197-2456(01)00131-3     Document Type: Article

References (17)

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5. Estimation and sample size considerations for clustered binary responses
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8. Estimating logistic regression parameters for bivariate binary data
9. Tests of hypotheses in overdispersed poisson regression and other quasi-likelihood models
10. A cautionary note on inference for marginal regression models with longitudinal data and general correlated response data
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13. Comment
14. On some small sample properties of generalized estimating equation estimates for multivariate dichotomous outcomes