Converting code to R Question
Here's a direct translation: Variable <- 0 Variable <- ifelse(item1 == 1, Variable +1, Variable) Variable <- ifelse(item2 == 1, Variable +1, Variable) Variable <- ifelse(item3 == 1, Variable +1, Variable) Variable <- ifelse(item4 == 1, Variable +1, Variable) Here's another way to do it: Variable <- 0 + (item1 == 1) + (item2 == 1) + (item3 == 1) + (item4 == 1) Note that I haven't worried about missing data - do you have NAs in your items? If you do, and you want NA to be not equal to 1 (rather than equal to NA): Variable <- sum((item1 == 1), (item2 == 1) , (item3 == 1) , (item4 == 1), na.rm=TRUE) Jeremy
On 25 February 2013 17:02, Craig J <cjohns38 at gmail.com> wrote:
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
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Old SPSS code sample
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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 .
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