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From |
Constantine Daskalakis <C_Daskalakis@mail.jci.tju.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Binomial confidence intervals |

Date |
Tue, 07 Sep 2004 14:41:24 -0400 |

At 02:17 PM 9/7/2004, Roberto G. Gutierrez, StataCorp wrote:

I do not think this is correct. For the CI, it is the parameter space, not the sample space, that matters (and the former is continuous). In other words, if we have k successes out of N trials, we are looking for limits {p_l, p_u}, such thatThe exact interval used by -ci, binomial- is the Clopper-Pearson interval, but you must realize that "exact" is a bit of a misnomer. It is exact in the sense that it uses the binomial distribution as the basis of the calculation. However, the binomial distribution is a discrete distribution and as such its cumulative probabilities will have discrete jumps, and thus you'll be hard pressed to get (say) exactly 95% coverage.

Pr [K <= k | p_l] = a/2

and

Pr [K >= k | p_u] = a/2

In general, there exist such limits that correspond to tail probabilities of (exactly) a/2. The fact that the sample space is highly discrete (when N is small) has nothing to do with it. The only exception is when the observed number of successes is either 0 or N; in that case, one limit is on the boundary of the parameter space (p_l=0 or p_u=1) and the corresponding tail probability on that side is exactly 0, not a/2 (as the manual correctly points out).

Or, am I missing something?

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Constantine Daskalakis, ScD

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Biostatistics Section, Thomas Jefferson University,

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**References**:**Re: st: Binomial confidence intervals***From:*rgutierrez@stata.com (Roberto G. Gutierrez, StataCorp)

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