Confidence Intervals, Binomial, When no Events are Observed
2
First published: 15 July 2005
No abstract is available for this article.
Bibliography
-
Hanley, J. A. &
Lippman-Hand, A.
(1983).
If nothing goes wrong, is everything allright? Interpreting zero numerators,
Journal of the American Medical Association
249,
1743–1745.
-
Jovanovic, B. &
Levy, P. S.
(1997).
A look at the rule of three,
American Statistician
51,
137–139.
-
Jovanovic, B. &
Viana, M. A. G.
(1997).
Upper confidence bounds for binomial probability in safety evaluation.
American Statistical Association 1996 Proceedings of the Section on Biopharmaceuticals.
American Statistical Association,
Alexandria.
-
Jovanovic, B. &
Zalensky, R.
(1997).
Upper bound on binomial probability when the number of observed events is small or zero,
Annals of Emergency Medicine
30,
301–306.
-
Kerns, J. R.,
Shaub, T. B. &
Fontanarosa, P. B.
(1993).
Emergency cardiac testing in the evaluation of emergency department patients with atypical chest pain,
Annals of Emergency Medicine
22,
794–798.
-
Louis, T. A.
(1981).
Confidence intervals for a binomial parameter after observing no successes,
American Statistician
35,
154.
-
Press, S. J.
(1989).
Bayesian Statistics: Principles, Models and Applications.
Wiley,
New York.
-
Vollset, S. E.
(1993).
Confidence intervals for a binomial proportion,
Statistics in Medicine
12,
809–824.