I'm learning R and am converting some code from SPSS into R. My background is in SAS/SPSS so the vectorization is new to me and I'm trying to learn how to NOT use loops...or use them sparingly. I'm wondering what the most efficient to tackle a problem I'm working on is. Below is an example piece of code. Essentially what it does is set a variable to zero, loop through item responses, and add one if a condition is met. For example, if item one was responded as a 1 then add one to the final variable. If item two was responded as a 2 then add one to the final variable. I have to do this for five scales with each scale having 6 items half of which may have the 1 response pattern and half the 2 pattern.
Any suggestions on how best to tackle this in R would be helpful. Craig ********** Old SPSS code sample ********** Compute Variable = 0. IF (item1 = 1) Variable = Variable +1 . IF (item2= 2) Variable = Variable +1 . IF (item3 = 1) Variable = Variable +1. IF (item4 = 2) Variable = Variable +1. EXECUTE . [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.