similar to: Sample size for 2-sample proportion tests

Please forgive me, I feel exceptionally like a newbie. Although I've read screeds of documentation, I just can't see how this is done. I have a data frame that contains a number of pass/fails for certain variable sizes. From that, I would like to form another data frame that contains the proportions of pass/fails per variable. So, for example: df <- data.frame( Var=c(3,3,3,4,4),

All, I have been digging around in the help files and found bsamsize in Hmisc, but I am wondering if i am using it right. So, here is the question: given a binomial response (success/failure) for 2 groups (treatment/control) and I want to estimate the necessary sample size (n) to determine if the magnitude of the difference between treatments and controls is a 25% increase in success

Hi, I' am doing a stats project using R to work out the size of a t-test and wilcoxon test depending on the distribution and sample size. I just can't get it to work - I want to put my results from the function size() into an array.At the moment I keep getting the error message:Error in res[distribution, test, samplesize] <- results : subscript out of boundsCan anyone tell me where

Hi, I'm doing a stats project using R to work out the size of a t-test and wilcoxon test depending on the distribution and sample size. I just can't get it to work - I want to put my results from the function size() into an array.At the moment I keep getting the error message:Error in res[distribution, test, samplesize] <- results : subscript out of boundsCan anyone tell me where

Hi, I'm trying to get better at things like lapply but it still stumps me. I have a function I've written, tested and debugged using individual calls to the function, ala: ResultList5 = DoAvgCalcs(IndexData, Lookback=5, SampleSize=TestSamples , Iterations=TestIterations ) ResultList8 = DoAvgCalcs(IndexData, Lookback=8, SampleSize=TestSamples , Iterations=TestIterations ) ResultList13

Here is the function that makes the data.frames in the list: funweek <- function(df) if (length(df$elapsed_time) > 5) { res = fitdist(df$elapsed_time,"exp") year = df$sale_year[1] sample = df$sale_week[1] mid = df$m_id[1] estimate = res$estimate sd = res$sd samplesize = res$n loglik = res$loglik aic = res$aic bic = res$bic chisq =

I am trying to use R to do loglogistic hazard estimation. My plan is to generate a loglogistic hazard sample data and then use survreg to estimate it. If everything is correct, survreg should return the parameters I have used to generate the sample data. I have written the following code to do a time invariant hazard estimation. The output of summary(modloglog) shows the factor loading of

Hi Hugo, I've been able to replicate your bug, including for other distributions (runif, rexp, rgamma, etc) which shouldn't be surprising since they're probably all drawing from the same pseudo-random number generator. ?Interestingly, it does not seem to depend on the choice of seed, I am not sure why that is the case. I'll point out first of all that the R-devel mailing list is

Hi Hugo, I've been able to replicate your bug, including for other distributions (runif, rexp, rgamma, etc) which shouldn't be surprising since they're probably all drawing from the same pseudo-random number generator. ?Interestingly, it does not seem to depend on the choice of seed, I am not sure why that is the case. I'll point out first of all that the R-devel mailing list is

Dear R helpers exposure <- data.frame(id = c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20), ead = c(9483.686,50000,6843.4968,10509.37125,21297.8905,50000,706152.8354, 62670.5625, 687.801995,50641.4875,59227.125,43818.5778,52887.72534,601788.7937, 56813.14859,4012356.056,1419501.179,210853.4743,749961,6599.0862), pd =

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

Hello, guys! I'm a novice at programming, learning about the speex and its applications now. Specifically, my current goal is to encode microphone input on iOS device in real-time, saving result to a file frame-by-frame. So far, I've managed to: 1) compile speex static library (it works, at least for iPhone/iPad, but not on iOS simulator; this is fine for now); 2) encode pcm data from

I was experiencing a strange pattern of slowdowns when using sample.int(), where sampling from a one population would sometimes take 1000x longer than taking the same number of samples from a slightly larger population. For my application, this resulted in a runtime of several hours rather than a few seconds. Looking into it, I saw that sample.int() is hardcoded to switch algorithms when the

Dear R users, I am trying to simulate some multitrait-multimethod models using the packages sem and psych but whatever I do to deal with models which do not converge I always get stuck and get error messages such as these: "Error in summary.sem(M1) : coefficient covariances cannot be computed" "Error in solve.default(res$hessian) : System ist f?r den Rechner singul?r: reziproke

Dear colleague, I not sure this R code is correctly ? I would to show the number of Sample Size at Sample Size Axis that line draw from Power Axis (80%) from R code. How I show this and select the most appropriate of this power (.79955687 - 80983575). Thank for your help and answer. Best Regards, Nikom Thanomsieng, Email: nikom at kku.ac.th .... #Power analysis: Sample size for

I generate random vector from Weibull distribution sampWB <-urweibull(sampleSize, shape=shape.true, scale=scale.true, lb=0, ub=Inf) how can I create subvector containing 30% of samplesize of sampWB which should be assigned as Censored data? The probability for each value in sampWB can be uniform to be included in the subvector.

Hi I'm conducing a meta-analysis using the meta package. Here's a bit of code that works fine - tmp <- metacont(samplesize.2, pctdropout.2, sddropout.2, samplesize.1, pctdropout.1, sddropout.1, data=Dataset, sm="WMD") I would now like to control for a couple of variables (continuous and categorical) that aren't in the equation. Is meta

sampleSize <- 20 shape.true <- 1.82 scale.true <- 987 sampWB <- rweibull(sampleSize, shape=shape.true, scale=scale.true) print(sampWB) censidx <- sample(1:length(sampWB), length(sampWB)*0.3) Censored.data <- sampWB[censidx] noncensidx <- defines the rest values of the vector which is not included at Censored.data? [[alternative HTML version deleted]]