Type 1 Rank correlation coefficient based test on positive dependence through stochastic ordering
Description
This function evaluates the assumption of positive dependence through stochastic ordering in multiple comparison procedures
Usage
coco1(cordx, cordy, alpha = 0.05, Rboot = 100, seed = 1)
Arguments
cordx
a numeric vector
cordy
a numeric vector
alpha
a number of significance level
Rboot
a number of bootstrap replicates
seed
a number of the seed of random number generator
Details
R package boot is included for computing nonparametric bootstrap confidence intervals
Value
a vector of three numbers: a lower bound of one-sided confidence interval lower_bound, a test statistic estimation, and an indicator whether the PDS condition holds or not PDS_assumption
Author(s)
Jiangtao Gou
Fengqing Zhang
References
Gou, J., Wu, K. and Chen, O. Y. (2024). Rank correlation coefficient based tests on positive dependence through stochastic ordering with application in cancer studies, Technical Report. Gou, J. (2023). On dependence assumption in p-value based multiple test procedures. Journal of Biopharmaceutical Statistics, 33(5), 596-610. Gou, J. (2024). A test of the dependence assumptions for the Simes-test-based multiple test procedures. Statistics in Biopharmaceutical Research, 16(1), 1-7.
Examples
set.seed(123)
cordx <- rnorm(40)
cordy <- rnorm(40)
coco1(cordx, cordy)
Type 2 Rank correlation coefficient based test on positive dependence through stochastic ordering
Description
This function evaluates the assumption of positive dependence through stochastic ordering in multiple comparison procedures
Usage
coco2(cordx, cordy, alpha = 0.05, Rboot = 100, seed = 1)
Arguments
cordx
a numeric vector
cordy
a numeric vector
alpha
a number of significance level
Rboot
a number of bootstrap replicates
seed
a number of the seed of random number generator
Details
R package boot is included for computing nonparametric bootstrap confidence intervals
Value
a vector of three numbers: a lower bound of one-sided confidence interval lower_bound, a test statistic estimation, and an indicator whether the PDS condition holds or not PDS_assumption
Author(s)
Jiangtao Gou
Fengqing Zhang
References
Gou, J., Wu, K. and Chen, O. Y. (2024). Rank correlation coefficient based tests on positive dependence through stochastic ordering with application in cancer studies, Technical Report. Gou, J. (2023). On dependence assumption in p-value based multiple test procedures. Journal of Biopharmaceutical Statistics, 33(5), 596-610. Gou, J. (2024). A test of the dependence assumptions for the Simes-test-based multiple test procedures. Statistics in Biopharmaceutical Research, 16(1), 1-7.
Examples
set.seed(123)
cordx <- rnorm(40)
cordy <- rnorm(40)
coco2(cordx, cordy)