similar to: how to extract data from a function printout - example provided

Dear R users, I am trying to estimate to estimate the average treatmen effect on the treated (ATT) using first the MatchIt software to weight the data set and, after this, the Zelig software as shown in Ho et al. (2007). See here for an explanation of how to apply this technique in R: http://imai.princeton.edu/research/files/matchit.pdf I encounter a slight problem when I apply the weights that

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"),

Hi there, I'm wondering what Zelig in the following situation (code below) actually does. Is this considered as a so called regression adjustment after the propensity score matching? library(MatchIt) library(Zelig) data(lalonde) re78 represents the outcome variable 1. With Zelig m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree + re74 + re75, data = lalonde)

Dear R-Users, I have a problem on extracting T-Stat and P-Value. I have written R-code below library("Matching") data("lalonde") attach(lalonde) names(lalonde) Y <- lalonde$re78 Tr <- lalonde$treat glm1 <- glm(Tr~age+educ+black+hisp+married+nodegr+re74+re75,family=binomial,data=lalonde) pscore.predicted <- predict(glm1) rr1 <-

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]

I'm using the "Match" package to do propensity score matching. Here's some example code that shows the problem that I'm having (much of this code is taken from the Match package documentation): *data(lalonde) glm1 <- glm(treat~age + I(age^2) + educ + I(educ^2) + black + hisp + married + nodegr + re74 + I(re74^2) + re75 + I(re75^2) + u74 + u75,

Hi there, I guess this is an easy one, but still:  I would like to randomly sample 0s and 1s but in a way that I end up having for example 70% of 1s and the rest of 0s and not 50:50 as this function does: sample(c(0,1), 100, replace = TRUE) Any recommendations? Many thanks! Ana [[alternative HTML version deleted]]

Hi there, Could anyone please help me to understand what should be done in order not to get this error message: Error: evaluation nested too deeply: infinite recursion / options(expressions=)? Here is my code: determinant<- function(x){det(matrix(c(1.0,0.2,0.5,0.8,0.2,1.0,0.5,0.6,0.5,0.5,0.5,1.0,x,0.8,0.6,x,1.0),ncol=4,byrow=T))} matrix<-

This may be a really obvious question but I just can't figure out how to do it. I have a small dataset that I am trying to compare to some controls. It is essential that the controls are matched on Cancer Stage (a numerical factor between 1 and 4), and then ideally on Age (integer), Gender (factor), Performance Status(factor). I'm using matchit to try and do this, but it seems to give

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

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

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

Let's say I have an original data set which is called A and data extracted from this original data set, called B. Based on these A and B data set I would like to get data set C which includes all the remaining data from the data set A after we exclude data of the data set B. Any idea how to do this? [[alternative HTML version deleted]]

Hi there, Anyone has an idea how to put those two sets of code together so that I can get a 3-dimensional picture that includes points instead of 2 separate pictures which doesnt make that much sense at the end. #Let's say that these are the data we would like to plot: A<-c(62,84,53) B<-c(64,82,55) C<-c(56,74,41) D<-c(46,68,38) E<-c(71,98,72) data<-rbind(A,B,C,D,E)

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,

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

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:

I have to the treatment effect base on the observational data.And the treatment variable is multinomial rather than binary.Because the treatment assignment is not random,so the selection-bias exists.Under this condition,what's the best way to estimate the treatment effect? I know that if the treatment is binary,I can use propensity score matching using MatchIt package.But what about

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