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Confidence intervals for secondary parameters following a sequential test
Author(s) -
Whitehead John,
Todd Susan,
Hall W. J.
Publication year - 2000
Publication title -
journal of the royal statistical society: series b (statistical methodology)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.523
H-Index - 137
eISSN - 1467-9868
pISSN - 1369-7412
DOI - 10.1111/1467-9868.00260
Subject(s) - frequentist inference , confidence interval , statistics , null hypothesis , point estimation , interim , interval estimation , credible interval , mathematics , statistical hypothesis testing , confidence distribution , interim analysis , coverage probability , computer science , econometrics , bayesian probability , bayesian inference , medicine , alternative medicine , pathology , archaeology , history
In sequential studies, formal interim analyses are usually restricted to a consideration of a single null hypothesis concerning a single parameter of interest. Valid frequentist methods of hypothesis testing and of point and interval estimation for the primary parameter have already been devised for use at the end of such a study. However, the completed data set may warrant a more detailed analysis, involving the estimation of parameters corresponding to effects that were not used to determine when to stop, and yet correlated with those that were. This paper describes methods for setting confidence intervals for secondary parameters in a way which provides the correct coverage probability in repeated frequentist realizations of the sequential design used. The method assumes that information accumulates on the primary and secondary parameters at proportional rates. This requirement will be valid in many potential applications, but only in limited situations in survival analysis.