search for: matchit

...an'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 equal priority to all my variables so I can be relatively well matched on Age, Sex and PS but not exactly matched on Stage. Stage is the biggest influence on outcome... so I must match it as close to perfect as possible even if that means dropping some data...

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 im...

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 im...

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 as.data.frame...

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/optmat...

...) 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 appreciated. Have a good day. Ana Here is the code: library(MatchIt) f <- treat ~ age + I(age^2) + educ + I(educ^2) + black + hispan +     married + nodegree + re74 + I(re74^2) + re75 + I(re75^2) d <- lalonde m <- "nearest" matching <- function(formula,data,method){           library(MatchIt)           m.out <- matchit(formula=f, data=d...

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=&...

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]]

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. How can I do that? Any help wo...

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"), model=&quo...

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)...

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 "suggests" rather than "depends" becuase much of the package works without it. If a user wants the functionality which requires matchit functions, we prompt them to install it. Our proble...

...9; >? $HOME', reason 'Invalid argument' In SPSS: GET ? FILE='C:\Users\Kimberley\Documents\WB Somalia\R Testing\Bor Ber Sheik Ainabo merged -and hacked - Copy.sav'. DATASET NAME DataSet1 WINDOW=FRONT. SET SEED = 1234. SET PRINTBACK=NONE. Loading required package: MASS ## ##? MatchIt (Version 2.4-20, built: 2011-10-24) ##? Please refer to http://gking.harvard.edu/matchit for full documentation ##? or help.matchit() for help with commands supported by MatchIt. ## Package SparseM (0.97) loaded. ?? To cite, see citation("SparseM") Warning message: In library(cem, logica...

...all of these to NA, regardless of the cause of the missing data. I am trying to do propensity score matching with this data, but it will not calculate the propensity scores, regardless of which method I have tried. I have tried the following methods: 1. Optimal propensity score matching, using the MatchIt library: m.out<-matchit(assignment~totalexp + yrschool+new+cert+age+STratio + percminority+urbanicity+povproblem+numthreats+numbattack+weight, data = data, distance="logit", method = "optimal", ratio = 1) 2. Nearest neighbor propensity score matching, using the MatchIt librar...

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 are produced in the st...

Good afternoon Running R2.10.0 on Windows I have a data frame that includes (among much else) a factor (In_2006) and a continuous variable (math_3_4). I would like to find the 2 cases for In_2006 = 0 that are closest to each case where In_2006 = 1. My data looks like In_2006 math_3_4 0 55.1 1 51.6 1 18.1 1 26.6 1 14.1

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, a...

...s(filename, type=?source?, repos=NULL) Entonces, encuentra el paquete, pero luego me dice que no puede abrir un directorio y no realiza la instalación. También he probado a hacerlo directamente desde el repositorio, y me da el mismo error. Mi problema principal es que necesito instalar el paquete ?MatchIt? y cuando empieza la instalación me dice que no puede instalar la dependencia ?optmatch? porque en el repositorio hay una versión posterior a la que necesita. ¿Alguien me puede ayudar? Muchas gracias Pepe Martín

....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 multinomial? Maybe one way is the method proposed by Imbens,2000,The role of the propensity score in estimating dose-response functions,Biometrika,87:706-710.But I can't find any R function to do the task.So I hope the lister can give me some suggestions. Thank you in...

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) z.out <- zelig(re78 ~ distance, data = match.data(m.out, "control"), model = "ls"...