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Dear R users, As a new comer to R, I would like to create a new variable using if statements but don't know how to do it. Basically, I have two variables (EvHint and MinTex). I want to create a third variable called RiskTest. In SPSS, my syntax would look like Compute RiskTest=0. if (EvHint=1 & MinTex=1) RiskTest=1. Question: How do I do this with R? My Data EvHint<-c(0, 0, 0, 1,

Hello all, I al trying to join (ADD FILES in SPSS) two files using the rbind() function. However, with rbind() R does not behave the same way as SPSS. I mean, it just concatenates the two blocs with no consideration for same variables if these are not in the same position in the two files. Anyone knows a function that performs the SPSS ADD FILES task? Thanks, V [[alternative HTML version

hello there, I am trying to use a weight variable in a factor analysis but apparently the factanal command does not have a weight option. Any way to this? Thanks for your suggestions, V [[alternative HTML version deleted]]

All, I have the attached dataset which I read from SPSS and transformed a little bit using the attached script. I am trying to run a logistic regression using glm() on a subset of my data. When I run the logistic regression on the whle dataset, it runs OK. As soon as I try to run on the subset, I get an error message related to different lengths of variables. Any idea why this might be so? Thanks

Dear R users Happy New year to all for a start. Below is some data that I ran a factor analysis on. Using $score prints the scores for each of the three factors. However, I would like to access those factors as variable for new computations. How do I do that? In SPSS we just call fact1_1, fact2_1 etc.. Thanks for your suggestions. V ============ v1 <- c(1,1,1,1,1,1,1,1,1,1,3,3,3,3,3,4,5,6) v2

Dear all, I am looking for an equivalent of the pairwise.t.test() function using a complex survey design. Any suggestions on this or how to account for weights using the pairwise.t.test itself? Thanks, V [[alternative HTML version deleted]]

Hello, excuse me if this is trivial. I have some survey data with the following design MyDesign<-(id=ident, weights=~fwgt, fcp=~nval1+nval2, data=hh_data1) I would like to run simple frequency tables such as those provided by the freq() function of rgrs to check the impact of the sampling design on my Ns. Anyway I can do this? thanks, V [[alternative HTML version deleted]]