Multiple Hypotheses Testing for Discrete Data
The adjusted p-values for Modified Benjamini-Hochberg (BH) step-up FDR...
Calculating p-values for discrete data
The adjusted p-values for Gilbert-Tarone-BH step-up FDR controlling pr...
The adjusted p-values for Gilbert-Tarone-BY step-up FDR controlling pr...
The adjusted p-values for Modified Benjamini-Liu (BL) step-down FDR co...
The adjusted p-values for Modified Bonferroni single-step FWER control...
The adjusted p-values for Modified Benjamini-Yekutieli (BY) step-up FD...
The adjusted p-values for Modified Hochberg step-up FWER controlling p...
The adjusted p-values for Modified Holm step-down FWER controlling pro...
MHTdiscrete: A package for Multiple Hypotheses Testing for Discrete Da...
The adjusted p-values for Mixed Bonferroni single-step FWER controllin...
The adjusted p-values for Roth's step-up FWER controlling procedure.
The number of rejected hypotheses for Roth's step-up FWER controlling ...
The adjusted p-values for Sidak single-step FWER controlling procedure...
The adjusted p-values for Tarone's single-step FWER controlling proced...
The adjusted p-values for Tarone-Holm step-down FWER controlling proce...
A comprehensive tool for almost all existing multiple testing methods for discrete data. The package also provides some novel multiple testing procedures controlling FWER/FDR for discrete data. Given discrete p-values and their domains, the [method].p.adjust function returns adjusted p-values, which can be used to compare with the nominal significant level alpha and make decisions. For users' convenience, the functions also provide the output option for printing decision rules.