analyse.realdata2: Compute p-value for the overall treatment effect and for the...

In svetlanache/rapids: What the Package Does (One Line, Title Case)

Compute p-value for the overall treatment effect and for the interaction effect between the treatment and the predicted sensitivity status, for real data.

Description

significance level of the test for the sensitive group is determined by the input proportion of the significance level for the sensitive group (group.prop.sig) out of the overall significance (sig). The p-value for the overall treatment effect is computed using bivariate logistic regression with treatment allocation as a predictor. The p-value for the interaction effect between the treatment and the predicted sensitivity status is computed using bivariate logistic regression with the treatment effect, the effect for the predicted sensitivity status and the interaction effect.

Usage

analyse.realdata2(
  datalist,
  nclust,
  sig = 0.05,
  group.prop.sig = 0.2,
  seed = NULL,
  plotrs = F
)

Arguments

datalist	A list made up of 3 data frames (patients and covar) and a vector of binary responses, for real data (see realdata object): patients (a data frame with patients information), covar (a data frame with the covariates), response (a vector of responses).
nclust	Number of clusters
sig	An overall significance level for the adaptive design.
group.prop.sig	Proportion of significance level for the sensitive group test.
seed	A seed for the random number generator.
plotrs	An indicator whether to plot the risk scores (default = FALSE).

Value

An object of class "rapids".

patients: A data frame with patients inormation.

pval.resp: P-value for the overall test for the treatment effect w.r.t. response 1

pval.resp2: P-value for the overall test for the treatment effect w.r.t. response 2

stat.resp.group: Statistic for the interaction effect between the treatment and the predicted cluster (w.r.t. response ), a vector of length nclust

pval.resp.group: P-value for the interaction effect between the treatment and the and the predicted cluster (w.r.t. response 2), a vector of length nclust

stat.resp2.group: Statistic for the interaction effect between the treatment and the predicted cluster (w.r.t. response), a vector of length nclust

pval.resp2.group: P-value for the interaction effect between the treatment and the predicted cluster (w.r.t. response 2), a vector of length nclust

estimate.rr: Estimated rate of responsein the sensitive group on the treatment arm.

estimate.rr2: Estimated rate of response 2 in the sensitive group on the treatment arm.

cvrs: A matrix of the risk scores (rows = patients, columns = simulations).

cvrs2: A matrix of the risk scores 2(rows = patients, columns = simulations).

cluster.pred: Predicted clusters

Author(s)

Svetlana Cherlin, James Wason

See Also

analyse.simdata2, simulate.data2 and cvrs.plot functions; print and plot methods.

Examples

sig = 0.05
nclust = 4
group.prop.sig = 0.2
seed = 123
plotrs = T
realres.cvrs2 = analyse.realdata2(realdata2, nclust, sig, group.prop.sig, seed, plotrs)

svetlanache/rapids documentation built on Sept. 15, 2023, 7 a.m.