qvSUDT {DunnettTests} | R Documentation |
In multiple testing problem, the adjusted P-values correspond to test statistics can be used with any fixed alpha to dertermine which hypotheses to be rejected.
qvSUDT(teststats,alternative="U",df=Inf,corr=0.5,corr.matrix=NA,mcs=1e+05)
teststats |
The k-vector of test statistics, k≥ 2 and k≤ 16. |
alternative |
The alternative hypothesis: "U"=upper one-sided test (default); "L"=lower one-sided test; "B"=two-sided test. For lower one-sided tail test, use the negations of each of the test statistics. |
df |
Degree of freedom of the t-test statistics. When (approximately) normally distributed test statistics are applied, set df=Inf (default). |
corr |
Specified for equally correlated test statistics, which is the common correlation between the test statistics, default=0.5. |
corr.matrix |
Specified for unequally correlated test statistics, which is the correlation matrix of the test statistics, default=NA. |
mcs |
The number of monte carlo sample points to numerically approximate the probability that to solve critical values for a given P value, refer to Equation (3.3) in Dunnett and Tamhane (1992), default=1e+05. |
Return a LIST containing:
"ordered test statistics" |
ordered test statistics from smallest to largest |
"Adjusted P-values of ordered test statistics" |
adjusted P-values correspond to the ordered test statistics |
FAN XIA <phoebexia@yahoo.com>
Charles W. Dunnett and Ajit C. Tamhane. A step-up multiple test procedure. Journal of the American Statistical Association, 87(417):162-170, 1992.
qvSUDT(c(2.20,2.70),df=30)