[DDI-users] DDI-users Digest, Vol 105, Issue 6 (SAS/Stata extended missings)

[Adrian Dușa]

Yes I understand the need for the special values, and your answer just
confirms what I had thought: they're needed only to avoid <accidental>
treatment as valid values.

This shouldn't be the case, however, if the researcher really knows what to
do.
As you say, in SPSS the value -1 can be declared as missing, and in R one
could simply calculate the mean of a vector excluding the negative values,
or create a copy of the entire dataset where all the negative values are
replaced with NAs.

This is simply a matter of procedure, which is software independent.
However, <special> numeric values are not software independent, while using
DDI as a common gateway should (in principle) be universal, rather than
specific.

No matter what the software package is, when a researcher is careful to
replace the respective negative values with missings, there would be no
mistakes... which kind of works along my argument with cross-portability.

The DDI file could contain only valid numeric values, and then researchers
might convert those to any kind of special missings depending on software.

Adrian


On Tue, Jun 24, 2014 at 4:56 PM, Hoyle, Larry <larryhoyle at ku.edu> wrote:

>  In SAS and Stata the values ._   .a - .z are special numeric values,
> treated as missing, which compare less than the smallest valid value.
>
>
>
> If you use -1, for example, to represent “refused” and compute a mean on
> the variable the -1 will be included in the computation – not ignored.
>
> Using a scheme like
>
> value timetopg
>
> 1 = '1-2 mos'
>
> 2 = '3-5 mos'
>
> 3 = '6-12 mos'
>
> 4 = ' > 1 yr'
>
> .r = 'Refused'
>
> .d = "don't  remember"
>
> .s  = 'set to missing by rule'
>
> .o = 'other missing'
>
> ;
>
>
>
> Would allow you to compute statistics ignoring the missing values as well
> as tabulations using the missing values (e.g. computing the % refused).
>
>
>
> In packages like SPSS one can specify that otherwise valid values (like -1
> in your example) can be treated as missing. The advantage of using “out of
> band” values is that they cannot accidentally be treated as valid values.
>
>
>
> R, I believe, only has two missing values: NA and NaN. In order to prevent
> treating -1 - -4 as valid values in your example in R you would need to
> transform the variable to convert all of these values to NA.  If you are
> moving data from any software that allows multiple missing values SPSS, SAS
> or Stata to R you may need to use NA as the missing value for all of the
> categories and perhaps create a secondary variable preserving the different
> values of missing.
>
>
>
>
>
>
>
> --- Larry Hoyle
>
>
>
>
>
> *From:* ddi-users-bounces at icpsr.umich.edu [mailto:
> ddi-users-bounces at icpsr.umich.edu] *On Behalf Of *Adrian Du?a
> *Sent:* Tuesday, June 24, 2014 4:03 AM
> *To:* Data Documentation Initiative Users Group
> *Subject:* Re: [DDI-users] DDI-users Digest, Vol 105, Issue 6 (SAS/Stata
> extended missings)
>
>
>
> Hi Bob,
>
>
>
> I've never used SAS, but have to ask something regarding these different
> types of missings.
>
> Is there any particular advantage of .r, .d and .m over something like:
>
>
>
> value timetopg
>
> 1 = '1-2 mos'
>
> 2 = '3-5 mos'
>
> 3 = '6-12 mos'
>
> 4 = ' > 1 yr'
>
> -1 = 'Refused'
>
> -2 = "don't  remember"
>
> -3 = 'set to missing by rule'
>
> -4 = 'other missing'
>
> ;
>
>
>
> I'm thinking about cross portability of these codes, and the above
> suggestion would work (I think) in every statistical package while .d and
> .r etc are specific for SAS only.
>
>
>
> Thanks,
>
> Adrian
>
>
>
>
>
>
>
> On Mon, Jun 23, 2014 at 7:49 PM, Bob McConnaughey <bobmcconn at gmail.com>
> wrote:
>
> i suspect i'm belaboring the obvious here, but here's how SAS treats
> numeric missings
>
> SAS numeric missings appear to be "character strings" - but they are
> treated, within SAS (and Stata i believe) as "invented" numbers, smaller
> than the "smallest" negative number.  eg -1*10**10000 > .z > .a > . > ._ ;
>  (though i don't think i've ever seen "._" used).  However their great
> virtues are: 1. As "known" missings they automatically get excluded from
> computations involving the variable they represent.  And, like any other
> value (character or numeric) the can be described using formats..  That is
> when you do, say, a frequency proc and assign formats to the missing you'd
> see something like:
>
> time_to_pregnancy1
>
> value timetopg
>
>   1-2 = '1-2 mos'
>
>   3-5 = '3-5 mos'
>
>   6-12 = '6-12 mos'
>
>  13-high = ' > 1 yr'
>
>  .r         = 'Refused'
>
>  .d        = "don't  remember"
>
>  .m       = 'set to missing by rule'
>
> .          = 'other missing'
>
> ;
>
> Value labels are the equivalent SPSS feature (i think..i haven't used SPSS
> in 35 yrs) and even now most of our original questionnaires use "out of
> range" numbers for special missing values.  But the number of times
> post-docs and researchers have come up with funky basic descriptive
> statistics because, oh, "99" was used for a missing value for
> "height_inches" is well nigh uncountable.  And matters are getting worse
> because there's a general tendency to not use codebooks any more;  instead
> projects rely on "annotated questionnaires" and SAS "proc contents" I am
> very much hoping to get people here to go back to using codebooks and the
> various DDI products SHOULD be convincing. (well, convincing for people
> other than the small group of reproductive epidemiology researchers I work
> with most closely).
>
>
>
> thanks for the responses!
>
> Bob McC....
>
> "At times like this, an adult needs a drink."
> Dance, Dance, Dance.  H. Murakami
>
>
>
>
>
>
>
>
> _______________________________________________
> DDI-users mailing list
> DDI-users at icpsr.umich.edu
> http://lists.icpsr.umich.edu/mailman/listinfo/ddi-users
>
>
>
>
>
> --
>
> Adrian Dusa
> University of Bucharest
> Romanian Social Data Archive
> 1, Schitu Magureanu Bd.
> 050025 Bucharest sector 5
> Romania
> Tel.:+40 21 3126618 \
>         +40 21 3120210 / int.101
> Fax: +40 21 3158391
>
> _______________________________________________
> DDI-users mailing list
> DDI-users at icpsr.umich.edu
> http://lists.icpsr.umich.edu/mailman/listinfo/ddi-users
>
>


-- 
Adrian Dusa
University of Bucharest
Romanian Social Data Archive
1, Schitu Magureanu Bd.
050025 Bucharest sector 5
Romania
Tel.:+40 21 3126618 \
        +40 21 3120210 / int.101
Fax: +40 21 3158391
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://lists.icpsr.umich.edu/pipermail/ddi-users/attachments/20140624/346574f2/attachment.html