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Approximate Is Better than "Exact" for Interval Estimation of Binomial Proportions
Alan Agresti and Brent A. Coull
The American Statistician
Vol. 52, No. 2 (May, 1998), pp. 119-126
Stable URL: http://www.jstor.org/stable/2685469
Page Count: 8
You can always find the topics here!Topics: Confidence interval, Statistics, Binomials, Proportions, Sample size, Probabilities, Interval estimators, Standard error, Inference, Mathematical intervals
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For interval estimation of a proportion, coverage probabilities tend to be too large for "exact" confidence intervals based on inverting the binomial test and too small for the interval based on inverting the Wald large-sample normal test (i.e., sample proportion ± z-score × estimated standard error). Wilson's suggestion of inverting the related score test with null rather than estimated standard error yields coverage probabilities close to nominal confidence levels, even for very small sample sizes. The 95% score interval has similar behavior as the adjusted Wald interval obtained after adding two "successes" and two "failures" to the sample. In elementary courses, with the score and adjusted Wald methods it is unnecessary to provide students with awkward sample size guidelines.
The American Statistician © 1998 American Statistical Association