Statistics in Medicine · 2007 · 252 citations · 31 references
Public HealthBiostatisticsExperimental DesignMeta-analysisStatisticsConfidence IntervalsEffect Size EstimationHypothesis TestingPower AnalysisStatistical AnalysisBootstrap Confidence IntervalsConfidence Interval AnalysisConfidence Interval ConstructionConfidence Interval EstimationConfidence Interval EvaluationEffect Size AnalysisLognormal RegressionSmall-sample Confidence Intervals
Confidence interval construction is preferred over significance testing, yet many effect measures lack satisfactory methods in small to moderate samples. The authors propose a general approach for estimating differences between effect measures. The method also yields confidence limits for risk ratios and lognormal means. Numerical evaluation demonstrates that the closed‑form procedure outperforms existing methods, including the bootstrap. © 2007 John Wiley & Sons, Ltd.
Abstract It is widely accepted that confidence interval construction has important advantages over significance testing for the presentation of research results, as now facilitated by readily available software. However, for a number of effect measures, procedures are either not available or not satisfactory in samples of small to moderate size. In this paper, we describe a general approach for estimating a difference between effect measures, which can also be used to obtain confidence limits for a risk ratio and a lognormal mean. Numerical evaluation shows that this closed‐form procedure outperforms existing methods, including the bootstrap. Copyright © 2007 John Wiley & Sons, Ltd.
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Bootstrap confidence intervals
Thomas J. DiCiccio, Bradley Efron · Statistical Science · 1996 · 2.3K citations · Full text
Comparative analysis of two rates
Olli S. Miettinen, Markku Nurminen · Statistics in Medicine · 1985 · 1.1K citations