Simultaneous confidence intervals for sequentially rejective multiple test procedures
Calculates simultaneous confidence intervals for sequentially rejective multiple test procedures.
simConfint(object, pvalues, confint, alternative=c("less", "greater"),
estimates, df, alpha=0.05, mu=0)object |
A graph of class |
pvalues |
A numeric vector specifying the p-values for the sequentially rejective MTP. |
confint |
One of the following:
A character string |
alternative |
A character string specifying the alternative hypothesis, must be "greater" or "less". |
estimates |
Point estimates for the parameters of interest. |
df |
Degree of freedom as numeric. |
alpha |
The overall alpha level as numeric scalar. |
mu |
The numerical parameter vector under null hypothesis. |
For details see the given references.
A matrix with columns giving lower confidence limits, point estimates and upper confidence limits for each parameter. These will be labeled as "lower bound", "estimate" and "upper bound".
Kornelius Rohmeyer rohmeyer@small-projects.de
Frank Bretz, Willi Maurer, Werner Brannath, Martin Posch: A graphical approach to sequentially rejective multiple test procedures. Statistics in Medicine 2009 vol. 28 issue 4 page 586-604. http://www.meduniwien.ac.at/fwf_adaptive/papers/bretz_2009_22.pdf
est <- c("H1"=0.860382, "H2"=0.9161474, "H3"=0.9732953)
# Sample standard deviations:
ssd <- c("H1"=0.8759528, "H2"=1.291310, "H3"=0.8570892)
pval <- c(0.01260, 0.05154, 0.02124)/2
simConfint(BonferroniHolm(3), pvalues=pval,
confint=function(node, alpha) {
c(est[node]-qt(1-alpha,df=9)*ssd[node]/sqrt(10), Inf)
}, estimates=est, alpha=0.025, mu=0, alternative="greater")
# Note that the sample standard deviations in the following call
# will be calculated from the pvalues and estimates.
ci <- simConfint(BonferroniHolm(3), pvalues=pval,
confint="t", df=9, estimates=est, alpha=0.025, alternative="greater")
ci
plotSimCI(ci)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.