similar to: General help on sample size based on recurrent events

I'm trying to fit a Cox proportional hazards model to some hospital admission data. About 25% of the patients have had at least one admission, and of these, 40% have had two admissions within the 12 month period of the study. Each patients has had one of 4 treatments, and one of the treatment groups has had no admissions for the period. I used:

Dear R-helpers, I’m writing for advice on whether I should use R or a different package or language. I’ve looked through the R-help archives, some manuals, and some other sites as well, and I haven’t done too well finding relevant info, hence my question here. I’m working with hierarchical data (in SPSS lingo). That is, for each case (person) I read in three types of (medical) record: 1.

Dear R-listers, I am a relatively inexperienced R-user currently migrating from Stata. I am deeply frustrated by this data manipulation question: I know how I could do it in Stata, but I cannot make it work in R. I have a data frame of hospitalization data where each row represents an admission. I need to know when patients were first discharged, but the problem is that patients were sometimes

Dear R-users! I am using R 1.7.0, under Windows XP. Having some hospital discharge data (admission date and discharge date for each patient), I want to get the number of patients in the hospital on a given date. My data look like (simple example): > x <- data.frame(patid=c("pat1", "pat2"), adm.date = c("15.03.2002", "16.03.2002"),

Hello, I have a cohort with approx 1,200 patients at the ages of 30-65 that had their first myocardial infarction during 1992: · They were in a follow up until 2005. · About 400 of them died during this period of time (right censored) · Each one of them had up to 4 mi recurrent events. I am using the semi-parametric model in order to assess the relationship of

Hi all, Again I have searched the net and so on, without finding an answer to this surely simple problem. A short bit of code would be appreciated. I have a object named `data' with the following column headings. Date, maxitemp, minitemp, admissions, d.o.w. Where d.o.w. is day of the week, written "Sun" "Mon" etc. I just need to scale the Monday admissions by

Hi all, I have a large data.frame, 1530 observation with 6 columns. I want to merge a 7th column, a transformation of the response variable (hospital admissions), namely trans<-sqrt(copd$admissions+0.25) trans<-data.frame(trans) And now when I do copd2<-merge(copd,trans) (copd being my original data.frame), R either crashes or is taking an extremely long time to do the computation. I

Hi, I'm trying to estimate a (parametric) competing risks model in the context of duration (or survival, if you wish) analysis. That is, instead of studying the transition of subjects to "death", I wish to study the transitions to multiple *destinations* (which is different from studying multiple *durations*, or recurrent events). I am more interested in the hazard function rather

Hi, I am wondering if there is a simple way to plot MCF(mean cumulative function) for recurrent events in R? MCF (http://www.weibull.com/hotwire/issue57/relbasics57.htm) And do you have some other recommendation in visualize recurrent events? I did some research online. Some people use ggplot2 to plot MCF, but it requires some additional coding. http://user2010.org/slides/Shentu.pdf Your help

I'd like to program a simulation of recurrent events to test few models in R. Is there anybody who has experience of that and could give me advice? Your help is greatly appreciated! Regards, -- Peggy Ramlau ramlau at gmx.de +493080906358 Bitte l?cheln! Fotogalerie online mit GMX ohne eigene Homepage!

Hi all, Firstly I appologise if this question has been answered previously, however searching of the archives and the internet generally has not yielded any results. I am looking in to the effects of summer weather conditions (temperature, humidity etc), on the incidences of a breathing disorder brought on through smoking (COPD). I am fairly new to R and completely new to the idea of

Dear R Community: I am working on a public health early warning system, and I see that the qcc package allows for CUSUM and other statistical quality tests but I am not sure if my project is a good match for qcc functions as written. Any advice you may have is very much appreciated. I have four years worth of daily counts of emergency room admissions for different conditions (e.g. respiratory,

Dear All, I'm a relative novice in R, with some experience with S-plus and quite a bit in SAS. In R and S-Plus, I've primarily worked with Frank Harrell's Design and Hmisc libraries. I have R 2.3.1 for windows (XP) installed. I have a project coming up in which the outcome will be recurrent events. There will be right censoring and likely to be a good stack of 0s on the left.

I''m trying to get my routes to work properly. Here''s how I''m defining one of my routes: map.downloads '':category/downloads'', :controller => ''downloads'', :action => ''list_downloads_for_category'', :requirements => {:category => DownloadableFileCategory.category_regex} And here''s the method

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Hi R users,I am a beginner in the use of R. I need urgent help for my thesis study. <https://stats.stackexchange.com/posts/633206/timeline> I have daily air pollution parameters PM10, PM2.5 CO, NO2, SO2, and O3. I also have daily hospital admission numbers. Taking into account the effect of weekends and holidays, I would like to used generalised additive model (GAM) to explore the

Hi , I have a data set with recurrence time (up to four) of myocardial infarction (MI). Part of the file is showing below: Num1 Trt Sex Time T1 T2 T3 T4 1011 1 1 9 1211 0 1 59 3020 1 2 14 3 1245 0 1 18 12 16 3069 1 2 26 6 12 13 2051 0 1 53 3 15 46 51 The data consist of the following eight variables: Num1 , patient number Trt, treatment group (1=placebo and 2=drug) Sex,

Dear all, I am having difficulties using the seemingly-simple function lag. I have a dataframe with several weather variables (maxitemp, windspeed, rainfall etc), and the response variable (admissions). The dataset is fairly large (1530 observations). I simply want to model the response against a lag of a couple of the explanatory variables, say maxitemp and rainfall. I would like to look at

Dear R gurus, particularly those of generous M$ tolerance and diverse gifts and knowledge! I have an interesting challenge that I will end up crunching in R involving service usage by patients. Maybe I can do all of it in R but I can't see how yet. My situation is that our IT Department can give me loads of XLS files about patients one of our services have seen. The are one per patient

Test =) soddsjbmshdwqwu -- Test, yep.