mpe.t.test: Intersection-Union t-Test for Testing Multiple Co-Primary...

Description Usage Arguments Details Value References See Also Examples

View source: R/mpe.t.test.R

Description

The function computes the intersection-union t-test which forms the basis for the sample size and power calculations in function power.unknown.var.

Usage

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mpe.t.test(X, Y, conf.level = 0.975)

Arguments

X

matrix with observations of group 1 in rows

Y

matrix with obersvations of group 2 in rows

conf.level

confidence level of the interval.

Details

The function computes the intersection-union t-test which forms the basis for the sample size and power calculations for continuous multiple co-primary endpoints with unknown covariance as computed by function power.unknown.var. The implementation is based on the formulas given in the references below.

The null hypothesis reads μ_Tk-μ_Ck <= 0 for at least one k in {1,...,K} where Tk is treatment k, Ck is control k and K is the number of co-primary endpointss (i.e. number of columns of X and Y).

Value

Object of class "mpe.test".

References

Sugimoto, T. and Sozu, T. and Hamasaki, T. (2012). A convenient formula for sample size calculations in clinical trials with multiple co-primary continuous endpoints. Pharmaceut. Statist., 11: 118-128. doi:10.1002/pst.505

Sozu, T. and Sugimoto, T. and Hamasaki, T. and Evans, S.R. (2015). Sample Size Determination in Clinical Trials with Multiple Endpoints. Springer Briefs in Statistics, ISBN 978-3-319-22005-5.

See Also

power.unknown.var

Examples

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delta <- c(0.25, 0.5)
Sigma <- matrix(c(1, 0.75, 0.75, 1), ncol = 2)
n <- 50
X <- rmvnorm(n=n, mean = delta, sigma = Sigma)
Y <- rmvnorm(n=n, mean = rep(0, length(delta)), sigma = Sigma)
mpe.t.test(X = X, Y = Y)

Example output

Loading required package: mvtnorm

	Intersection-union t-test

data:  x and y
t = 1.1913, df = 98, p-value = 0.2364
alternative hypothesis:  true difference in means is larger than 0 for all endpoints 
97.5 percent confidence intervals:
             0.025         1
EDP.1 -0.231250687 0.7390239
EDP.2  0.008666703 0.9112800
sample estimates:
              X         Y
EDP.1 0.3871769 0.1332903
EDP.2 0.6033859 0.1434126

mpe documentation built on May 2, 2019, 2:04 a.m.