search for: genmatch

Dear R Users, I am a novice learner of R software. I am working with Genetic Matching - GenMatch(), but I am getting an Error message as follows:  Error in GenMatch(Tr = Tr, X = X.binarynp, BalanceMatrix = BalanceMatrix.binarynp,  :    GenMatch(): input includes NAs Could you please suggest me correcting the above problem? My GenMatch command is, > gen1 <- GenMatch(Tr = Tr, X = X.bin...

Dear R Users, I am a novice learner of R software. I am working with Genetic Matching - GenMatch(), but I am getting an Error message as follows:  Error in GenMatch(Tr = Tr, X = X.binarynp, BalanceMatrix = BalanceMatrix.binarynp,  :    GenMatch(): input includes NAs Could you please suggest me correcting the above problem? My GenMatch command is, > gen1 <- GenMatch(Tr = Tr, X = X.bin...

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 <-

To anyone who uses the Match() function in the Matching library... How do you go about deciding how many matches you will use? With my data, my standard errors generally get smaller if I use more matches. Speaking of standard errors, when correcting for heteroscedasticity, how many matches do you use (this is the Var.cal option). It seems to me that it might make sense to use the same number

Hello! I need to compare 2 datasets whether they come from the same distribution. I use function ks.boot{Matching}. And what is the confidence level of the p-value, returned by ks.boot function? The code is: set=read.table("http://stella.sai.msu.ru:8080/~gala/data/testsets.csv", header=T,sep=',') set1=set[!is.na(set$set1),'set1']

Dear R users, I am trying to do exact matching on a large dataset (500.000 obs), about equal size of treatment and controll group, with replacement: As for the moment I use the "Match" function of the "Matching" library. I match on 2 covariates and all observations in the treatment group have at least one exact counterpart in the controllgroup. Now I want to introduce