On Nov 19, 2011, at 6:31 PM, Anthony Staines wrote:
Dear colleagues,
I would be very grateful for your help with the following. I have
banged my head off this question several times in the past, and
repeatedly over the last week. I have looked in the usual places and
found no obvious solution. I fear that this just means I didn't
recognize it, but I'd be very grateful for your help.
I am scoring 8000 psychometric tests - the SCQ, if you have heard of
it. On this test the scoring rules depends on one variable SCQ1 - if
this is answered yes, the final score is a function of 39 variables,
and if no, of 31 variables.
I've calculated both of these scores (SCQScore1 and SCQScore2)for
all the children in my study, and I wish to create a final score,
which is SCQScore1 when SCQ1 is 1, and SCQScore2 when SCQ1 is 2.
There are also missing values for SCQ1, and I have chosen, for the
moment, to set the final score to SCQScore1 for these. [[This is a
debatable choice, but I am not asking your advice on that choice!]]
This would seem to be an obvious task for ifelse()
SCQScore <- NA
d$SCQScore <- ifelse( SCQ1 == 1, d$SCQScore1, d$SCOScore2)
(And don't use 99 for missing. Use NA. It will protect you better than
"99".)
I suppose you could enforce the two level testing with:
d$SCQScore <- ifelse( SCQ1 == 1, d$SCQScore1,
ifelse(SCQ1 ==2, d$SCOScore2, NA))
d$SCQScore <- 99
##Distinct value for any other values I've missed
d$SCQScore[SCQ1 == 1] <- d$SCQScore1[SCQ1 == 1]
## Talks using phrases/sentences, so sum S2CQ:SCQ40
d$SCQScore[SCQ1 == 2] <- d$SCQScore2[SCQ1 == 2]
## Can't do this, so sum SCQ8:SCQ40
d$SCQScore[is.na(d$SCQ1)] <- d$SCQScore1 [is.na(d$SCQ1)]
## SCQ1 is missing
This fails on line 2
(d$SCQScore[SCQ1 == 1] <- d$SCQScore1[SCQ1 == 1])
with the error message
"NAs are not allowed in subscripted assignments",
presumably because SCQ1 does indeed contain missing values.
This can be fixed, got around, or otherwise bypassed, by creating a
new variable SCQ1, with no missing values, as shown :-
SCQ1 <- d$SCQ1
SCQ1[is.na(SCQ1)] <- 3
d$SCQScore[SCQ1 == 1] <- d$SCQScore1[SCQ1 == 1]
## Talks using phrases/sentences so sum S2CQ:SCQ40
d$SCQScore[SCQ1 == 2] <- d$SCQScore2[SCQ1 == 2]
## Can't do this, so sum SCQ8:SCQ40
d$SCQScore[SCQ1 == 3] <- d$SCQScore1[SCQ1 == 3]
## We don't know if he/she can talk, so guess - sum S2:S40
This type of thing is a common problem in my little world. Is there
a better/less klutzy/smarter way of solving it than creating a new
variable each time? Please bear in mind that it is critical, for
later analysis, to keep the missing values in SCQ1.
Best wishes,
Anthony Staines
--
Anthony Staines, Professor of Health Systems,
School of Nursing and Human Sciences, DCU, Dublin 9,Ireland.
Tel:- +353 1 700 7807. Mobile:- +353 86 606 9713
http://astaines.eu/
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David Winsemius, MD
West Hartford, CT
______________________________________________
R-help@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
