R: Sample Size Computation Based on a Global Procedure in the...
global.1m.ssc
R Documentation
Sample Size Computation Based on a Global Procedure in the Context of Multiple Continuous Endpoints
Description
This function computes the sample size with a global method in the
context of m multiple continuous endpoints. Two groups are
considered: C for control and T for treatment. The clinical aim
is to be able to detect a mean difference between the test and the control product
for at least one endpoint among m. This method is based on a
multivariate model with co-variates taking into account
the correlations between the endpoints.
Usage
global.1m.ssc(method, mean.diff, sd, cor, v = NULL, M = NULL,
power = 0.8, alpha = 0.05)
Arguments
method
either "Model" if no co-variates are involved and "Adj.Model" for a model with co-variates.
mean.diff
vector of the mean differences of the m
endpoints between both groups under the alternative hypothesis.
sd
vector of the standard deviations of the m
endpoints. These are assumed identical for both groups.
cor
correlation matrix between the endpoints. These are assumed identical for both groups.
v
v is a p\times1 vector whose l^{th}
component is v_{l}=ar{a}_{l}^C-ar{a}_l^T, where p is
the number of adjustment variables, and ar{a}_{l}^{i} is the
mean of the adjustment variable a_{l} for the group i,
i = C, T.
M
M is a p\times p matrix with general term M_{l,l'}=≤ft(overline{a_la_{l'}}^C-ar{a}_l^Car{a}_{l'}^C
ight)+≤ft(overline{a_{l}a_{l'}}^T-ar{a}_l^Tar{a}_{l'}^T
ight).
power
value which corresponds to the chosen power.
alpha
value which correponds to the chosen Type-I error rate bound.
Value
Sample size
The required sample size.
Author(s)
P. Lafaye de Micheaux, B. Liquet and J. Riou
References
Lafaye de Micheaux P., Liquet B., Marque S., Riou J. (2014). Power and
Sample Size Determination in Clinical Trials With Multiple Primary
Continuous Correlated Endpoints, Journal of
Biopharmaceutical Statistics, 24, 378–397.