overall.analysis: Overall statistics and inference
In pact: Predictive Analysis of Clinical Trials

Description Usage Arguments Details Value Author(s) Examples

Produces some statistics for the overall (non-predictive) comparison of the E and C for the same dataset for which the predictive model pact.fit was developed.

1	overall.analysis(p)

`p`	An object of class `pact`

Statistics for the overall comparison of the E and C is produced for the the data from a randomized clinical trial. The input is an object of class pact.

An list with the following components. As a side effect, these are also printed on screen

`family`	The response variable type used
`nobs`	The sample size
`n.E`	Number of subjects getting the new treatment
`n.C`	Number of subjects getting the control treatment
`LR`	The log-rank statistic for the overal difference in survival between E and C groups (for family="cox")
`LR.pval`	The p-value for LR based on the log-rank test (for family="cox")
`RR.E`	The response rate for group treated with E (new treatment) (for family="binomial")
`RR.C`	The response rate for group treated with C (Control) (for family="binomial")
`RRdiff.pval`	The chi-square test based pvalue for the difference in response rates (for family="binomial")

Jyothi Subramanian and Richard Simon
Maintainer: Jyothi Subramanian <subramanianj01@gmail.com>

data(prostateCancer)
Y <- prostateCancer[,3:4]
Xf <- prostateCancer[,7:8]
Xv <- prostateCancer[,c(5:6,9)]
Treatment <- as.factor(prostateCancer[,2])
p <- pact.fit(Y=Y, Xf=Xf, Xv=Xv, Treatment=Treatment, family="cox", varSelect="none")
overall.analysis(p)

### Binary response
data(EORTC10994)
Y <- as.factor(EORTC10994[,4])
Xv <- EORTC10994[,c(2,5:7)]
Treatment <- as.factor(EORTC10994[,3])
p <- pact.fit(Y=Y,Xv=Xv,Treatment=Treatment,family="binomial",varSelect="none")
overall.analysis(p)