Improved Trimmed Weighted Hochberg Procedures and Sample Size Optimization

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Documentation for package ‘itrimhoch’ version 1.0.0

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find_k_given_rho_target_mvtnorm Find the difference between the error rate when k and rho are both given and the prespecified alpha level
find_k_target_mvtnorm Find the difference between the error rate when k is specified and rho is optimal and the prespecified alpha level
find_rho_target_mvtnorm Find the partial derivative of the error rate with respect to the correlation coefficient rho when k and rho are given
iHpTarget1 Find the difference between the achieved power and the desired power for rejecting H1 using the improved trimmed or truncated weighted Hochberg procedure
iHpTarget1m Find the difference between the achieved power and the desired power for rejecting H1 using the improved trimmed or truncated weighted Hochberg procedure with allowance for different data maturities
iHpTarget2 Find the difference between the achieved power and the desired power for rejecting H2 using the improved trimmed or truncated weighted Hochberg procedure
iHpTarget2m Find the difference between the achieved power and the desired power for rejecting H2 using the improved trimmed or truncated weighted Hochberg procedure with allowance for different data maturities
interpolate_zero Calculate the x-coordinates of a function where zero crossings occur
itwcHochPower Power for rejecting H1 using various types of the Hochberg Procedure
optk The two-step algorithm to calculate the best k value for the improved trimmed Hochberg method to ensure that the maximum type I error rate reaches alpha exactly when rho is arbitrary
optrho Calculate the rho value that reaches the maximum type I error rate in the improved trimmed Hochberg method when k value is given
optsamplesize_iHp Compute the optimal sample size for the improved trimmed weighted Hochberg procedure
optsamplesize_iHpm Compute the optimal sample size for the improved trimmed weighted Hochberg procedure with allowance for different data maturities
optsamplesize_tHp Compute the optimal sample size for the weighted trimmed or truncated Hochberg procedure
optsamplesize_wHolmpm Compute the optimal sample size for the weighted Holm procedure with allowance for different data maturities
optsamplesize_wHp Compute the optimal sample size for the weighted Hochberg procedure
tHpTarget1 Find the difference between the achieved power and the desired power for rejecting H1 using the weighted trimmed or truncated Hochberg procedure
tHpTarget2 Find the difference between the achieved power and the desired power for rejecting H2 using the weighted trimmed or truncated Hochberg procedure
typeIerror_Simes_mvtnorm Calculate the type I error rate of the weighted Simes test
typeIerror_trimSimes_mvtnorm Calculate the type I error rate of the trimmed weighted Simes test
wHolmTarget1 Find the difference between the achieved power and the desired power for rejecting H1 using the weighted Holm procedure
wHolmTarget1m Find the difference between the achieved power and the desired power for rejecting H1 using the weighted Holm procedure with allowance for different data maturities
wHolmTarget2 Find the difference between the achieved power and the desired power for rejecting H2 using the weighted Holm procedure
wHolmTarget2m Find the difference between the achieved power and the desired power for rejecting H2 using the weighted Holm procedure with allowance for different data maturities
wHpTarget1 Find the difference between the achieved power and the desired power for rejecting H1 using the weighted Hochberg procedure
wHpTarget2 Find the difference between the achieved power and the desired power for rejecting H2 using the weighted Hochberg procedure