Abstract #300844

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JSM 2003 Abstract #300844
Activity Number: 104
Type: Invited
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300844
Title: Improved Small-Sample Confidence Intervals for Categorical Data
Author(s): Alan Agresti*+
Companies: University of Florida
Address: Dept. of Statistics, Gainesville, FL, 32611-8545,
Keywords: Wald confidence interval ; score confidence interval ; odds ratio ; proportions
Abstract:

"Exact" small-sample methods for categorical data are exact in terms of using probability distributions that do not depend on unknown parameters. However, they are conservative inferentially, having actual error probabilities for tests and confidence intervals that are bounded above by the nominal level. We examine the conservatism for interval estimation and suggest ways of reducing it, illustrating for the binomial proportion, the difference between two proportions, and the odds ratio. We also summarize simple ways of adjusting standard large-sample confidence intervals to improve dramatically their small-sample performance.

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