[R] Advice on recoding a variable depending on another which contains NAs

[David Winsemius]

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