similar to: matchit - can I weight the parameters?

I've been tweaking code for several days on and off in R, cut and pasting in from a text editor (I just leave them open all the time). I think I got something that was usable but then a powersurge tripped the fuses and unfortunately the machine I was working on doesn't have a UPS. Does R hold the command data in cache some place? I've purposefully not opened R since the crash so

I might be missing something really obvious, but is there an easy way to locate all non-unique values in a data frame? Example mydata <- numeric() mydata$id <- 0:8 mydata$unique <- c(1:5, 1:4) mydata$result <- c(1:3, 1:3, 1:3) > mydata $id [1] 0 1 2 3 4 5 6 7 8 $unique [1] 1 2 3 4 5 1 2 3 4 $result [1] 1 2 3 1 2 3 1 2 3 What I want to to be able to get some form of data output

I have some data which is censored and I want to determine the median. Its actually cost data for a cohort of patients, many of whom are still on treatment and so are censored. I can do the same sort of analysis for a survival curve and get the median survival... ...but can I just use the survival curve functions to plot an X axis that is $ rather than date? If not is there some other way to

I'm hoping I'm missing some (probably fundamental basic process) which might make my life easier! Lets assume I have a 3 column table summarizing results from a trial from three arms (Arm A, B and C). For each arm there will be a number of pieces of information to report. The simplest example might be to compare this to the demographic comparisons often seen in clinical traisl where you

Greetings fellow humans, I am attempting to export a text file after using the MatchIt package to match control with treatment subjects. I attempted to write.table and used the following syntax: "write.table(social,"shaka.txt",sep=" ",quote=FALSE,row.names=FALSE,col.names= FALSE)" But received the following error message: "Error in

UseRs, I tried to install the MatchIt package on Ubuntu 7.04. When loading required dependencies I got the following error message: Error in dyn.load(x, as.logical(local), as.logical(now)) : unable to load shared library '/usr/local/lib/R/site-library/optmatch/libs/optmatch.so': /usr/local/lib/R/site-library/optmatch/libs/optmatch.so: cannot map zero-fill pages: Cannot

I have a dataset which for the sake of simplicity has two endpoints. We would like to test if two different end-points have the same eventual meaning. To try and take an example that people might understand better: Lets assume we had a group of subjects who all received a treatment. The could stop treatment for any reason (side effects, treatment stops working etc). Getting that data is very

Hi there dear R users! Anyone knows why does matchit function returns error whenever the "hull" option is used (either "hull.both", "hull.control" or "hull.treat"). Things work well with all the rest of discard options. This is the error msg. >m.out.base <- matchit(formula=f, data=d, method=m, discard="hull.control") [1]

Before I go and do this another way - can I check if anyone has a way of looping through data in odfWeave (or possibly sweave) to do a repeating analysis on subsets of data? For simplicity lets use mtcars dataset in R to explain. Dataset looks like this: > mtcars mpg cyl disp hp drat wt ... Mazda RX4 21.0 6 160 110 3.90 2.62 ... Mazda RX4 Wag 21.0 6 160 110 3.90

I might have factored the gender. I'm not sure it would in any way be quicker. But might be to some extent easier to develop variations of. And is sort of what factors should be doing... # make dummy data gender <- c("Male", "Female", "Male", "Female") WC <- c(70,60,75,65) TG <- c(0.9, 1.1, 1.2, 1.0) myDf <- data.frame( gender, WC, TG ) #

Folks, I have a strange situation where: library(MatchIt) f <- function(d) { m <- matchit(treatment ~ lsales + major.industry, data=d, method="nearest", discard="hull.treat") treatmentfirms <- match.data(m, group="treat") list(m=m, treatmentfirms=treatmentfirms) } res <- f(ex) does not work at the match.data() call,

I may be doing this wrong! but I have a function which I have simplified a lot below. I want to pass some 'field names' of a data-frame to the function for it to then do some manipulation of. Here's my code: #build a simple dataset mydataset = data.frame (

Sorry I'm having one of those moments where I can't find the answer but I bet its obvious... I'm outputting my results to a file using sink() Is there a command simillar to php's echo command that would allow me to add some text to that file ie: dataFr$a = 1:10 dataFr$b = 2*1:10 sink ("filepath/filename.txt", split=T) #Show number of entries in vector a table

Do you receive RDS objects from unknown (untrusted) sources? ?? If not - the security issue is a non-issue as I understand it. On Thu, 16 May 2024, 16:21 Vega, Ann (she/her/hers) via R-help, < r-help at r-project.org> wrote: > I help to coordinate the USEPA's R user group. We have over 500 members > and our security officer has required us to update to R version 4.4.0 >

There are many techniques Callum and yours is an interesting twist I had not considered. Yes, you can specify what integer a factor uses to represent things but not what I meant. Of course your trick does not work for some other forms of data like real numbers in double format. There is a cost to converting a column to a factor that is recouped best if it speeds things up multiple times. The

We would like to announce the release of our software MatchIt, now available on CRAN. MatchIt implements a variety of matching methods for causal inference. Abstract: MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2004) for improving parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt implements a wide range of sophisticated

We would like to announce the release of our software MatchIt, now available on CRAN. MatchIt implements a variety of matching methods for causal inference. Abstract: MatchIt implements the suggestions of Ho, Imai, King, and Stuart (2004) for improving parametric statistical models by preprocessing data with nonparametric matching methods. MatchIt implements a wide range of sophisticated

On Thu, 1 Jun 2017, POLWART, Calum (COUNTY DURHAM AND DARLINGTON NHS FOUNDATION TRUST) via R-help wrote: > Before I go and do this another way - can I check if anyone has a way of > looping through data in odfWeave (or possibly sweave) to do a repeating > analysis on subsets of data? > > For simplicity lets use mtcars dataset in R to explain. Dataset looks like this: >

Hi, I'm sure this should be simple but I can't figure it out! I want to get the median survival calculated by the survfit function and use the value rather than just be able to print it. Something like this: library(survival) data(lung) lung.byPS = survfit(Surv (time, status) ~ ph.ecog, data=lung) # lung.byPS Call: survfit(formula = Surv(time, status) ~ ph.ecog, data = lung) 1

Hi! I'm trying to perform propensity score matching on survey data and so for each individual observation I have a statistical weight attached. My question is: is there a way within the package to consider these weights in the matching procedure? Thank you very much. -- Maria Cristina Maurizio [[alternative HTML version deleted]]