adaptive.test.critical.value.func

Matrix that contains the error probabilities for different values of the test statistics T1.doublebar and T.doublebar that is produced by the function jointcrit

critmat

Significance level at which the test is conducted (alpha = 0.05).

alpha

This is an internal function which takes in a matrix that contains the error probabilities for different values of the test statistics T1.doublebar and T.doublebar and finds the pair of critical values (k1,k) for T1.doublebar and T.doublebar which satisfy the following: (i) have a Type I error rate of at most alpha; (ii) among pairs of critical values that cannot be improved, the critical values are most equitable, dividing the chance of false rejection as equally as possible between the events T1.doublebar&gt;=k1 and T.doublebar&gt;=k.

Sensitivity analysis for case-control studies in which some cases may meet a more narrow definition of being a case compared to other cases which only meet a broad definition.  The sensitivity analyses are described in Small, Cheng, Halloran and Rosenbaum (2013, "Case Definition and Sensitivity Analysis", Journal of the American Statistical Association, 1457-1468).  The functions sens.analysis.mh and sens.analysis.aberrant.rank provide sensitivity analyses based on the Mantel-Haenszel test statistic and aberrant rank test statistic as described in Rosenbaum (1991, "Sensitivity Analysis for Matched Case Control Studies", Biometrics); see also Section 1 of Small et al.  The function adaptive.case.test provides adaptive inferences as described in Section 5 of Small et al.  The function adaptive.noether.brown provides a sensitivity analysis for a matched cohort study based on an adaptive test.  The other functions in the package are internal functions.

adaptive.test.critical.value.func: Critical values for adaptive test

Description

Usage

Arguments

Value

References