similar to: Problem with matchit() and zelig()

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

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)

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

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,

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 <-

Hello, I am attempting to "automate" a Bayesian normal linear regression using Zelig. Basically, I have a list containing several zelig() objects, each having a different formula, same data set, and same model (normal.bayes). My problem lies in the setx() method, where I am setting a numeric parameter to a value other than the mean. This is straightforward if I input the parameters

Hi! Does somebody out there has experience with the Zelig package from Harvard uni? I have a problem when trying to set the explanatory variables with setx Polytomous logistic regression: >z.out <- zelig(OPARS ~ v1+v2+v3+...+vn, model = "mlogit", data=heb) that's OK >x.out<-set(z.out) Error in seq.Date(along = object) : `from' must be specified #??? I have no date

I'm running an ordered logit in R with the Zelig package and am trying to calculate some predicted probabilities. However, I get the following error message. > x.low <- setx(mod, cars=1)Error in dta[complete.cases(mf), names(dta) %in% vars, drop = FALSE] : incorrect number of dimensions I googled this problem and couldn't find anything, minus a question by me on this same

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

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]

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.

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]]

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

Dear R-friends, I am trying to use the Zelig library to simulate the following model: z.out<-zelig(formula = y ~ x1*x2 + x3 + x4 + x5, model="ls", data = my.data, weights = my.weights) Since the regression is weighted before running the regression I used the procedure: zelig2ls <- function(formula, model, data, M, ...) { mf <- match.call(expand.dots = TRUE)

I've run an ordered logistic regression model in R with Zelig and am looking to calculate predicted probabilities. Zelig has a series of simple one line commands to generate the information I want on first differences and so forth. Unfortunately, I keep getting an error when running the zelig function and was wondering if there was a quick alternative for generating predicted probabilities for

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,

Hi I have the code like I show below. The problem here is that I have a setReplacementMethod to set the value of my class slot. However, this function doesn't work when I call it within another function definition (declared by setMethod) of the same class. I do not understand this behavior that much. I'm wondering how to make this work? Any help would be really appreciated. Thank you.