search for: cpower

I would like to do some power estimations for a log-rank two sample test and cpower seems to fit the bill. I am getting confused though by the man page and what the arguments actually mean. I am also not sure whether cpower takes into account censoring or not. Could anyone provide a simple example of how I would get the power for a set control/non-control clinical trial where ce...

Hi Group, I'm looking for a method to calculate sample size for a non-inferiority survival analysis. Initially I've used cpower() of Hmisc, switching the roles of type-I and type-II errors, as cpower() assumes no treatment difference as the null hypothesis. Now, I would like to introduce event rate difference under the null-hypothesis, and calculate sample size accordingly. Any ideas? (similar functionality exists in nBino...

It returns a chi-squared statistic with one degree of freedom. -- David Winsemius -------------- Original message ---------------------- From: Timthy Chang <henchao.chang at gmail.com> > > > >See the cpower() and spower() functions in Frank Harrell's Hmisc package > >on CRAN. > > > >HTH, > > > >Marc Schwartz > > How to calculate the p-value of Log rank test ?? > Thank you very much! > -- > View this message in context: > http://www.nabble.com/Log-...

we have some initial data from our field sampling. From the means and variances, we see your sampling field is much heterogeneous (not uniform). We are looking for a "R" program for sampling size determination. Right now, we are not good enough to write a whole "R" program, so please help. [[alternative HTML version deleted]]

useR's, I am trying to do a power calculation for a survival analysis using a logrank test and I need some help properly doing this in R. Here is the information that I know: - I have 2 groups, namely HG and LG - Retrospective analysis with subjects gathered from archival data over 20 years. No new recruitment of subjects and no estimated time to target accrual and accrual rate. - Survival

Does anyone have any ideas how I could do a power calculation for a log rank test. I would like to know what the suggested sample sizes would be to pick a difference when the control to active are in a ratio of 80% to 20%. Thanks Dan -- ************************************************************** Daniel Brewer, Ph.D. Institute of Cancer Research Email: daniel.brewer at icr.ac.uk

Dear R users, I am not asking questions specifically on R, but I know there are many statistical experts here in the R community, so here it goes my questions: Freedman (1982) propose an approximation of sample size/power calculation based on log-rank test using the formula below (This is what nQuery does): (Z(1-?/side)+Z(power))^2*(hazard.ratio+1)^2 N =