FSmdFWER.indept.cv: Critical values for Fixed Sequence mdFWER Controlling... In FixSeqMTP: Fixed Sequence Multiple Testing Procedures

Description

Given a set of pre-ordered test statistics and the corresponding p-values, returns critical values using the directional fixed sequence multiple testing procedures under independence (See Procedure 2 and Theorem 2 in Grandhi et al. (2016)). The function also provides an option to make decisions and determine the sign given a pre-specified significant level α and the test statistics.

Usage

 `1` ```FSmdFWER.indept.cv(p, test.stat, alpha=0.05, make.decision = TRUE) ```

Arguments

 `p` numeric vector of p-values (possibly with `NA`s). Any other R is coerced by `as.numeric`. Same as in `p.adjust`. `test.stat` numeric vector of test statistics, which are used to determine the direction of decisions, with the same length of `p`. `alpha` significant level used to compare with Critical values to make decisions, the default value is 0.05. `make.decision` logical; if `TRUE` (default), then the output include the decision rules compared original p-values with the critical values, and directions of the decision based on the sign of test statistics.

Value

A numeric vector of the critical values (of the same length as `p`) if `make.decision = FALSEALSE`, or a data frame including original p-values, critical values, test statistics and directional decision rules if `make.decision = TRUE`.

Yalin Zhu

References

Grandhi, A., Guo, W., & Romano, J. P. (2016). Control of Directional Errors in Fixed Sequence Multiple Testing. arXiv preprint arXiv:1602.02345.

`FSmdFWER.arbidept.cv` for fixed sequence mdFWER controlling procedures under arbitrary dependence.
 ```1 2 3 4``` ```## Clinical trial example in Grandhi et al. (2016) Pval <- c(0.0008, 0.0135, 0.0197, 0.7237, 0.0003, 0.2779, 0.0054, 0.8473) Zstat <- c(3.4434, 2.5085, 2.3642, -0.3543, 3.7651, 1.0900, 2.8340, 0.1930) FSmdFWER.indept.cv(p = Pval, test.stat = Zstat, make.decision = TRUE) ```