Gauss or Bernoulli?

Peter J. Hannan and David M. Murray
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Peter J. Hannan: University of Minnesota
David M. Murray: University of Minnesota

Evaluation Review, 1996, vol. 20, issue 3, 338-352

Abstract: This Monte Carlo study compares performance of the linear and the logistic mixed-model analyses of simulated community trials having event rates of 37%, 13%, or 5%, intraclass correlations between 0.01 and 0.05, and 17 or 5 denominator degrees of freedom. Type I or Type II error rates showed no essential difference between the two analysis methods. They showed depressed error rates when the event rate or the denominator degrees of freedom were small. The authors conclude that in studies with adequate denominator degrees of freedom, the researcher may use either method of analysis but should accept negative estimates of components of variance to avoid depression of error rates.

Date: 1996
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Persistent link: https://EconPapers.repec.org/RePEc:sae:evarev:v:20:y:1996:i:3:p:338-352

DOI: 10.1177/0193841X9602000306

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