[R] Converting code to R Question
William Dunlap
wdunlap at tibco.com
Tue Feb 26 02:51:16 CET 2013
Note that in
Variable <- 0 + (item1 == 1) + (item2 == 1) + (item3 == 1) + (item4 == 1)
the '0 +' is not needed, since adding logicals produces integers.
Your second solution
Variable <- sum((item1 == 1), (item2 == 1) , (item3 == 1) , (item4 == 1), na.rm=TRUE)
gives the wrong answer, since sum() always returns a scalar. You could treat logical
NA's as FALSE's by defining
is.true <- function(x) !is.na(x) & x
and using it as
Variable <- is.true(item1==1) + is.true(item2==1) + is.true(item3==1) + is.true(item4==1)
Bill Dunlap
Spotfire, TIBCO Software
wdunlap tibco.com
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf
> Of Jeremy Miles
> Sent: Monday, February 25, 2013 5:41 PM
> To: Craig J
> Cc: r-help
> Subject: Re: [R] 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
> >
> > **********
> > 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 at 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.
>
> ______________________________________________
> R-help at 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.
More information about the R-help
mailing list