similar to: matchit - can I weight the parameters?

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

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

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]

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,

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

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]]

Dear list; How can I speed up the run of following code (illustrative) #======================================================================== con<-vector("numeric") for (i in 1:limit) { if(matched data for the ith item found) { if(i==1) {con<-RowOfMatchedData } else {con<-rbind(con,matchedData)} } }

Hi there, Does anyone know how to extract data from a function that prints out two or more summaries? In the function below (the whole code is provided) we get 5 different tables of data. I would like to split each of these tables in a separate file (while the function itself shouldn't be changed), so that further analysis on each data set could be carried out. Your help is deeply

Hi! I am running a simulation testing group balance using different propensity score matching techniques. I am using the MatchIt package to match and analyze the data. Since I am running this analysis many, many times with different simulated data sets, I need to make the output from the MatchIt summary and put it into a dataset and then append each successive run to the end of that dataset.

Dear all, Does anybody know why the following code returns an error message? >library(MatchIt) >library(Zelig) >data(lalonde) > >m.out1<-matchit(treat~age+educ+black+hispan+nodegree+married +re74+re75, method="full", data=lalonde) > >z.out1<-zelig(re78~age+educ+black+hispan+nodegree+married+re74+re75, data=match.data(m.out1, "control"),

Hello, I am trying to use R for propensity score matching in SPSS.? I have version 21 of SPSS and I downloaded R 2.14.2 as directed as well as the R Essentials plug-in.? I have run a test for R and it appears to be running correctly.? I then downloaded psmatching3 and have tried to use the PS matching dialog in SPSS.? However, I continue to run into problems as SPSS reports that there is no

Hello! If I understand this listserve correctly, I can email this address to get help when I am struggling with code. If this is inaccurate, please let me know, and I will unsubscribe. I have been struggling with the same error message for a while, and I can't seem to get past it. Here is the issue: I am using a data set that uses -1:-9 to indicate various kinds of missing data. I changed

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

R-devel, There has been some confusion on the MatchIt package mailing list on the meaning of [--install=no] in the comment column of CRAN's automated package check. It's my understanding that, at the very least, a package marked like this will not have its test cases run each night. Are there other checks that are omitted? How, if at all, are such install flags related to the

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

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

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

Hola a todos! Espero que alguien me pueda echar algo de luz al problema que tengo. Estoy intentando instalar algunos paquetes antiguos en R (3.3.0), como ?devtools? en su penúltima versión, y me está resultando imposible. Instalé Rtools y R me dice que funciona, pero no consigo hacer que se instale el paquete. He probado bajando el paquete en formato .tar.gz y luego con las instrucciones: