bssr.gee.1subgroup {spass}

Blinded Sample Size Recalculation for longitudinal data in a One Subgroup Design

Description

Given re-estimations from an Internal Pilot Study (IPS), bssr.GEE.1subgroup re-estimates required sample size given the re-estimated nuisance parameters are given. bssr.gee.1subgroup is a wrapper for n.gee.1subgroup where the re-estimation of the variances can be highly dependable on the user and should be supplied separately. see "detail" for more information.

Usage

bssr.gee.1subgroup(
  alpha,
  tail = "both",
  beta = NULL,
  delta,
  estsigma,
  tau = 0.5,
  k = 1
)

Arguments

alpha

level (type I error) to which the hypothesis is tested.

tail

which type of test is used, e.g. which quartile und H0 is calculated.

beta

type II error (power=1-beta) to which an alternative should be proven.

delta

vector of estimated treatment effect in overall and sub population, c(overall population, only subpopulation).

estsigma

vector of re-estimated standard deviations, c(full population, subpopulation). See 'Details'.

tau

ratio between complementary F/S and sub-population S.

k

treatment allocation factor between groups: see 'Details'.

Details

This function provides a simple warped for n.gee.1subgroup where instead of initial assumptions, reestimated nuisance parameter are used. For more information see n.gee.1subgroup. Required samplesize to test alternative delta with specified power 1-beta when testing the global null hypothesis H_0: \beta_3^F=\beta_3^S=0 to level alpha is estimated. When testing outcomes have variance estsigma.

For sample sizes n_C and n_T of the control and treatment group respectively, the argument k is the sample size allocation factor, i.e. k = n_T/n_C and tau represents the ratio of the sub-population.

Value

bssr.gee.1subgroup returns a list containing the recalculated sample sizes along with all relevant parameters. Use summary.bssrest for a structured overview.

Source

bssr.gee.1subgroup uses code contributed by Roland Gerard Gera.

See Also

n.gee.1subgroup for sample size calculation prior to a trial and estimcov how the re-estimate nuisance parameters. See sim.gee for a working example for an initial sample size estimation and a re-estimation mid trial.

Examples

estimate<-bssr.gee.1subgroup(alpha=0.05,beta=0.2,delta=c(0.1,0.1),estsigma=c(0.8,0.4),tau=0.4, k=1)
summary(estimate)