similar to: sample size for log-rank test with more than 2 groups

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 censoring occurs at

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

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

A few months ago, I posted a query regarding code for a sample size estimate for a one arm survival trial. Below is some code I created to calculate such an estimate - perhaps it may be of some use. #cox.pow computes sample size for a one arm survival trial. med.0 is the null median #survival, med.a is the alternative median survival, a.time is the accrual time, and #f.time is the follow up

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

I have been trying to create code to calculate the power for an adaptive design with a survival endpoint according to the method of Schafer and Muller ('Modification of the sample size and the schedule of interim analyses in survival trials based on interim inspections,' Stats in Med, 2001). This design allows for the sample size to be increased (if necessary) based on an interim look at

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Hello Everyone,   I'm trying to conduct a couple of power analyses and was hoping someone might be able to help. I want to estimate the sample size that would be necessary to adequately power a couple of non-inferiority tests. The first would be a log-rank test and the second would be a Wilcoxon rank-sum test. I want to be able to determine the sample size that would be necessary to test for a

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 =

An earlier post had posed the question: "Does anybody know what is relation between 'T' value calculated by 'wilcox_test' function (coin package) and more common 'W' value?" I found the question interesting and ran the commands in R and SPSS. The W reported by R did not seem to correspond to either Mann-Whitney U, Wilcoxon W or the Z which I have more

Hello All, I want "Ranks' Table in R as like in SPSS ouput in the given link. http://www.statisticssolutions.com/methods-chapter/statistical-tests/kruskal-wallis-test/ Is the code is already available? Please let me know. Thanks, Lawrence

I'd like to make a less than full rank design using dummy variables for factors. Here is some example data: when <- data.frame(time = c("afternoon", "night", "afternoon", "morning", "morning", "morning", "morning", "afternoon", "afternoon"),

Dear all, I'm looking for someone that help me to write an R function to simulate survival data under complex situations, namely time-varying hazard ratio, marginal distribution of survival times and covariates. The algorithm is described in the reference below and it should be not very difficult to implement it. However I tried but without success....;-( Below there the code that I used; it

Hi R users, My goal is to rank my samples according to how they fall out in a histogram with 10 bins to produce a ranking for each sample according to where it falls on the histogram, with a "1" to represent one tail of the hist, a "10" to represent the other tail, and a "5" for the median/mean. I have a number of different data sets to do this with and in all cases

Dear all, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

Hi, I have a data.frame which is ordered by score, and has a factor column: Browse[1]> wc[c("report","score")] report score 9 ADEA 0.96 8 ADEA 0.90 11 Asylum_FED9 0.86 3 ADEA 0.75 14 Asylum_FED9 0.60 5 ADEA 0.56 13 Asylum_FED9 0.51 16 Asylum_FED9 0.51 2 ADEA 0.42 7 ADEA 0.31 17

Dear all, I know that when using R, people should have a sufficient level in statistics. As well, I'm not a genius, when dealing with logistic regressions. I would like to construct ICs, IPs, for a logistic regression, but the point is I have just 41 observations. I had a look at the Design package and noticeably the lrm function, but I'm still not able to reduce the IC's, as I

Hi, Im running samba-2.0.4b. Is there a way or granting access to shares using the NT SAM (global groups)? Currently I have to add users to the unix server, then add them to a GID. I hope there is an easier way! Thanks Mark Beck

Dear all, in last weeks you discussed about R vs SAS. I want to ask your opinion about a comparison between R and SPSS. I don't know this software, but some weeks ago I went to a presentation of this product. I found it really user-friendly with GUI (even if I'd prefer command line) and very usefull and simple to use in creation and managing tables, OLAP tecniques, pivot table. What you

Dear all, I have recently experienced something with the function order I cannot explain: The help(order) (which I admit having overlooked before) rises even more my confusion... The following lines made me think order() was returning the 'order' each value in a vector would take when sorted. > a <- c(4.1, 3.2, 6.1) > order(a) [1] 2 1 3 Doing > plot(a,