similar to: Retaining MatchIt output as a dataset

I have a categorical variable in a dataframe similar to the following... cat 1 1 3 2 4 I need to convert it to 4 dichotemous variables for each observations like... cat1 cat2 cat3 cat4 1 0 0 0 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 1 Thanks in advance! Shane

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

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]]

look at dev.new() to specify plot window size and then ?layout to specify number and size of each plot in the window Jiaqi.Zhang wrote > Hi, all, > > I am working on the following code to learn how to plot graphs together. I > used the par(mfrow=c(1,3)) function to try to put all three plot() graphs > together. But it always fail without any error message? Can anybody help

Hello, R friends... I am very new to R, and I need some help. I am trying to construct a simulation for my dissertation. I need to create 1000 datasets of 1000 subjects with the following variables... Treatment variable - Drawn from a binomial distribution (1 run, prob=.13) Covariate 1 - Drawn from a normal distribution (mean=100, sd=16) Covariate 2 - Drawn from a normal distribution

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

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

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

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

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

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]

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)

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

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'm new to R, but I'm trying to write a program for a dissertation that generates a dataset as follows... subject=1:1000 treat=rbinom(1*1000,1,.13) gender=rbinom(1*1000,1,.5) eth=runif(1*1000, min=1, max=4) cogat=rnorm(1*1000, 100, 16) map=rnorm(1*1000, 200, 9) simtest=data.frame (subject=subject, treat=treat, gender=gender, eth=round(eth,digits=0),

Dear All, I would like to find something ( references, code,..) to implement a comparison of three treatments in an observational study using the 'Propensity Score'. Any help is much appreciated. Thanks! Giovanni -- dr. Giovanni Parrinello Department of Biotecnologies Medical Statistics Unit University of Brescia Viale Europa, 11 25123 Brescia email: parrinel at med.unibs.it Phone:

On the topic of when to use "suggests" and "depends" and on R version requirements. I have cc'd this message to R-devel because I am curious about what senior developpers think about these issues. The problem arises because we are using some functions from the package "matchit" in a new version of our package "portfolio". We are listing the matchit in