Thanks again; It's ok I'm using the ldBands function now, the ld98.exe is just a small file to download into the path. I can calculate the alpha spending function and determine (given the Z statistics of my observations) if at the interim analysis the null hypothesis is to be rejected or not. But Does this function allow me to calculate the conditional power given the accumulating data? (I know they give the exit probabilities but is it those that I need?) and in the documentations they make a reference to another function using a bayesian method (Gaussian Bayesian Posterior and Predictive Distributions), but i'm not comfortable yet using the bayesian methods.
On Wed, 2007-03-28 at 10:49 -0500, Douglas Bates wrote: > On 3/28/07, Marc Schwartz <[EMAIL PROTECTED]> wrote: > > On Wed, 2007-03-28 at 02:42 -0700, francogrex wrote: > > > Does anyone know of an R package that is equivalent of S+SeqTrial for > > > analysis of clinical trials using group sequential methods? Thanks. > > > > I don't know that there are fully functional equivalents, but you might > > want to look at the following: > > > > 1. The GroupSeq package on CRAN: > > > > http://cran.r-project.org/src/contrib/Descriptions/GroupSeq.html > > > > > > 2. The ldBands() function in Frank Harrell's Hmisc package on CRAN: > > > > http://biostat.mc.vanderbilt.edu/s/Hmisc/html/ldBands.html > > > > This also requires the ld98 executable, which is available from: > > > > http://www.biostat.wisc.edu/landemets/ > > There is also the ldbounds package on CRAN for calculating Lan-DeMets > boundaries. It was prepared by students working with Dave DeMets and > does not require the ld98 executable. -- View this message in context: http://www.nabble.com/R-equivalent-of-S%2BSeqTrial--tf3478858.html#a9749485 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
