Date: Mon, 19 Jun 2006 16:22:03 -0400
Reply-To: "Howard Schreier <hs AT dc-sug DOT org>" <nospam@HOWLES.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: "Howard Schreier <hs AT dc-sug DOT org>" <nospam@HOWLES.COM>
Subject: Re: Filling of missing observations correctly in a dataset
I cannot remember whether David, before he went away, delegated
responsibility for telling people not to use arbitrary numeric values to
represent missing-value situations. So I'll jump in ...
Don't use arbitrary numeric values to represent missing-value situations.
It's all too easy to later run stats and forget to filter out such phony
cases. Garbage ensues.
The practice is common in environments which do not support missing value
indicators. SAS is not such an environment. In fact it supports 27 different
special missing values in addition to the generic MV, so qualitiative
differentiations can be recorded.
Venky reponse in this thread illustrates usage of the feature.
On Mon, 19 Jun 2006 08:26:13 -0700, Matt <mshall2@GMAIL.COM> wrote:
>I guess I'm not really sure why you would want to do this. If it is
>simply a matter of 'presenting' the data, I would, honestly do that in
>excel of another spreadsheet program.
>You would have to convert all your vars to character and then simply
>make an if-then to change . to NA/WD. I think you would be better off
>doing something like:
>
>array hr(5) Hr_4 Hr_8 Hr_12 Hr_24 Hr_36;
>do i=1 to 5;
> if Adm eq . then do;
> Adm = 98; /*where 98 eq WD*/
> do j=i to 5;
> hr(j) = 99; /*where 99 eq NA*/
> end;
> end;
> if Adm ne . AND hr[i] eq . then do;
> hr[i] = 98;
> do j=i to 5;
> hr[j] = 99;
> end;
> end;
>end;
>
>
>
>
>
>Madan Gopal Kundu wrote:
>> Hi all,
>>
>> =0D
>>
>> I have following dataset:
>>
>> =0D
>>
>> Pt Adm Pre Hr_4 Hr_8 Hr_12 Hr_24 Hr_36
>>
>> 4 36.9 36.5 36.4 37.2 36.2 36.4 37.1
>>
>> 5 36.3 . . . . . .
>>
>> 6 36.8 36.9 36.9 37 36.7 37.2 36.8
>>
>> 7 36.6 36.4 36.6 36.7 36.8 36.7 36.8
>>
>> 8 36.4 36.6 36.6 36.2 . . .
>>
>> 10 36.5 35.9 36.2 36.4 36 35.8 36.3
>>
>> 11 36.8 35.8 36.6 . . . .
>>
>> 12 36.4 36.1 36.4 36.8 36.3 36.2 36.6
>>
>> 13 36.6 36.2 36.3 36.5 36.4 36.3 36.6
>>
>> 14 36.5 36.8 37 37 36.6 36.8 36.8
>>
>> 15 36.3 . . . . . .
>>
>> =0D
>>
>> Now I have to fill the missing values in the above dataset smartly. I
>> have to report the above data in the following way:
>>
>> =0D
>>
>> 4 36.9 36.5 36.4 37.2 36.2 36.4 37.1
>>
>> 5 36.3 WD N/A N/A N/A N/A N/A
>>
>> 6 36.8 36.9 36.9 37 36.7 37.2 36.8
>>
>> 7 36.6 36.4 36.6 36.7 36.8 36.7 36.8
>>
>> 8 36.4 36.6 36.6 36.2 WD N/A N/A
>>
>> 10 36.5 35.9 36.2 36.4 36 35.8 36.3
>>
>> 11 36.8 35.8 36.6 WD N/A N/A N/A =0D
>>
>> 12 36.4 36.1 36.4 36.8 36.3 36.2 36.6
>>
>> 13 36.6 36.2 36.3 36.5 36.4 36.3 36.6
>>
>> 14 36.5 36.8 37 37 36.6 36.8 36.8
>>
>> 15 36.3 WD N/A N/A N/A N/A N/A
>>
>> =0D
>>
>> Here WD =3D Withdrawn, N/A =3D Not available
>>
>> Can anybody please help me by providing code of this conversion?
>>
>> Looking forwards for getting reply.=0D
>>
>> Thanks and Regards,
>>
>> Madan Gopal Kundu
>>
>> =0D
>>
>>
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