Journal ArticleDOI
Power/Sample Size Calculations for Generalized Linear Models
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In this paper, an approach for estimating power/sample size is described within the framework of generalized linear models, based on an asymptotic approximation to the power of the score test under contiguous alternatives and is applicable to tests of composite null hypotheses.Abstract:
An approach for estimating power/sample size is described within the framework of generalized linear models. This approach is based on an asymptotic approximation to the power of the score test under contiguous alternatives and is applicable to tests of composite null hypotheses. An implementation is described for the special case of logistic regression models. Simulation studies are presented which indicate that the asymptotic approximation to the finite-sample situation is good over a range of parameter configurations.read more
Citations
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Journal ArticleDOI
Power and sample size calculations. A review and computer program.
TL;DR: In this article, the sample size and power equations for these designs are shown to be special cases of two generic formulae for sample sizes and power calculations, and a computer program is available that can be used for studies with dichotomous, continuous, or survival response measures.
Journal ArticleDOI
A simple method of sample size calculation for linear and logistic regression
TL;DR: This paper suggests use of sample size formulae for comparing means or for comparing proportions in order to calculate the required sample size for a simple logistic regression model.
Journal ArticleDOI
Warfarin, aspirin, or both after myocardial infarction
TL;DR: Warfarin, in combination with aspirin or given alone, was superior to aspirin alone in reducing the incidence of composite events after an acute myocardial infarction but was associated with a higher risk of bleeding.
Book
Sample Size Calculations in Clinical Research
TL;DR: In this paper, the authors present a survey of sample sizes for single-arm and multiple-arm clinical trials, focusing on the following issues: Confounding and interaction: 1-Sided Test Versus Two-Sides Test Crossover Design Versus Parallel Design Subgroup/Interim Analyses Data Transformation Practical Issues COMPARING MEANS One-Sample Design Two-Sample Parallel Design 2-Sample Crossover design Multiple-Sample One-Way ANOVA Multiple-sample Williams Design Practical issues LARGE SAMPLE TESTS for PROPORTIONS
Journal ArticleDOI
Sample size determination for logistic regression revisited.
TL;DR: General Wald-based power and sample size formulas are derived and applied to minimize the total sample size in a case-control study to achieve a given power by optimizing the ratio of controls to cases.
References
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Book
Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI
Generalized Linear Models
TL;DR: In this paper, the authors used iterative weighted linear regression to obtain maximum likelihood estimates of the parameters with observations distributed according to some exponential family and systematic effects that can be made linear by a suitable transformation.
Journal ArticleDOI
Estimating the population attributable risk for multiple risk factors using case-control data
TL;DR: A straightforward and unified approach is presented for the calculation of the population attributable risk per cent in the general multivariate setting, with emphasis on using data from case-control studies, so that risks need not be estimated separately in a large number of strata.
Journal ArticleDOI
Logistic disease incidence models and case-control studies
Ross L. Prentice,R. Pyke +1 more
TL;DR: In this article, it was shown that the odds ratio estimators and their asymptotic variance matrices can be obtained by applying the original logistic regression model to the case-control study as if the data had been obtained in a prospective study.
Journal ArticleDOI
An Efficient and Portable Pseudo-Random Number Generator
B. A. Wichmann,I. D. Hill +1 more