search for: cody_hamilton

I would like to use R for submissions to FDA/CDRH (the medical device company I work for currently uses only SAS). Previous postings to the list regarding R and 21 CFR 11 compliance have been very helpful. However, reluctance to using open source software for statistical analyses and reporting remains high here at my company. Has anyone used R for an official submission to FDA/CDRH? It would

Does anyone know if for clinical studies the FDA would accept statistical analyses performed with R ? Delphine Fontaine

Following up to some extent on Friday's discussion regarding the 'validation' of R, could I ask the list group's opinion on possible advantages of R over Splus from a pharma/devices perspective? I wish to exclude the obvious price difference, which doesn’t seem to carry as much weight as I would have thought. Besides, I have noticed many former Splus users gravitating towards R,

Does anyone know of an R function for computing the Greenland-Robins variance for Mantel-Haenszel relative risks? Thanks Frank -- Frank E Harrell Jr Professor and Chair School of Medicine Department of Biostatistics Vanderbilt University

Is there a way to create a 'bubble plot' in R? For example, if we define the following data frame containing the level of y observed for 5 patients at three time points: time<-c(rep('time 1',5),rep('time 2',5),rep('time 3',5))

I am new to using R and would appreciate some advice on which books to start with to get up to speed on using R. My Background: 1-C# programmer. 2-Programmed directly using IMSL (Now Visual Numerics). 3- Used in past SPSS and Statistica. I put together a list but would like to pick the "best of" and avoid redundancy. Any suggestions on these books would be helpful (i.e. too much

...l-te-plait. Dirk -- Three out of two people have difficulties with fractions. ------------------------------ Message: 20 Date: Sun, 3 Aug 2008 08:30:47 -0800 From: "Franz Mueter" <fmueter at alaska.net> Subject: Re: [R] Bubble plots To: "'Cody Hamilton'" <Cody_Hamilton at Edwards.com>, <r-help at r-project.org> Message-ID: <000f01c8f586$496b4a10$dc41de30$@net> Content-Type: text/plain; charset="us-ascii" I believe ?symbols is what you are looking for. Of course, you need to convert categories to numeric values for plotting: For exampl...

...nd provide commented, minimal, self-contained, reproducible code. > ------------------------------ Message: 7 Date: Sun, 19 Aug 2007 08:50:17 -0700 (PDT) From: Thomas Lumley <tlumley at u.washington.edu> Subject: Re: [R] Regulatory Compliance and Validation Issues To: Cody Hamilton <Cody_Hamilton at Edwards.com> Cc: "r-help at stat.math.ethz.ch" <r-help at stat.math.ethz.ch> Message-ID: <Pine.LNX.4.64.0708190839120.18307 at homer24.u.washington.edu> Content-Type: TEXT/PLAIN; charset=US-ASCII; format=flowed On Fri, 17 Aug 2007, Cody Hamilton wrote: <snip> &g...

I am developing R code to implement the adaptive design approach of Schafer and Muller (Stats in Med 2001) for a survival endpoint. Would anyone be interested in collaborating with me on this code? I have fairly completed code, but would appreciate someone else's input on my work. Regards, -Cody

I came across a post by Karl Knoblick regarding the modeling of longitudinal data (see https://stat.ethz.ch/pipermail/r-help/2007-May/132137.html). I am often asked by physicians to perform what Karl refers to in his post as option 1: to perform paired t-tests against baseline at each follow up time point (30 days, 90 days, 6 months, etc.). Unlike Karl's example, however, many of the trials

I am running R version 2.4.1 on Windows XP. I have a question regarding the datadist() function from the Design library. I have a data.frame (call it my.data) with 4 columns. When I submit the code datadist(data=my.data) I get the following error message: Error in X[[1]] : subscript out of bounds I suspect there may be something wrong with my data.frame (I'm certain there is nothing

As I work as a biostatistician in the medical devices industry, I have been very happy to take part in several conversations on this list regarding the use of R in a regulated environment. It was with great interest, therefore, that I read the new guidance document for the use of R in regulated clinical trial environments now available on the R website. The purpose of the document is

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