[DDI-users] DDI-users Digest, Vol 105, Issue 14

[Bob McConnaughey]

Just fyi:
and i hope i'm not trying everybody's patience here.
Our datasets are generally a mix of demographic/behavioral variables + host
of "biologic" variables whether hormonal profiles of urine samples (daily
urines for up to 6 months in the study I've worked on for decades) or now,
for better or worse, oodles (the scientific term..) of genetic based vars -
there could be, literally, 1000s of snps for each subject. yuck. AND then
(far too many imo ;-) variables that attempt to capture all the various and
sundry "exposure" variables.
    we've working towards  a more or less standard set of SAS missing
values that attempt to deal with basic "missing situations" - but with the
long history of some of these projects, even now we're not completely
there, yet.
.r = 'respondent refused'
.d = "don't know"
.i  = "imputed deletion"
.  = "missing"  /* just missing from the qx or biological sample */
.l = "lost to followup"
.m = "missing portion of derived var"
 /* say a derived  rate of change var requires 5 days of progesterone     */
  /* hormone and only has 3 days in the sequence, .m could reflect that  */
(the above is not completely accurate - i'm at home w/ the world cup.
Character variables are different kettle of fish.

a simple study might be one i've worked on forever: Early Pregnancy Study
http://www.niehs.nih.gov/research/atniehs/labs/epi/studies/eps/index.cfm
a somewhat more complex study: Norway Facial Clefts
http://www.niehs.nih.gov/research/atniehs/labs/epi/studies/ncl/index.cfm
a horribly complex study on which i've not had to work much: Sisters Breast
Cancer Study
http://www.niehs.nih.gov/research/atniehs/labs/epi/studies/sister/index.cfm

As I've mentioned before, my ideal would be to convince everyone (besides
the PIs with whom i've worked most closely ) that having the excellent base
of documentation provided by various DDI based solutions (Nesstar,
Collectica (which i haven't worked with) is not just a good idea, but
necessary.  For many years we used a Cobo l/ Vax based codebook generation
which was MUCH better than nothing, although v. long in the tooth.  But
that was discarded ~ 14 yrs ago and I regard the replacement (annotated
questionnaires, SAS proc contents and various  modes of summarizing each
variable) as less than satisfactory.  But the missing values bit is the
most frequently used argument against DDI solutions.
Though I'm tempted to take frequencies of just the various missings for
each variable and paste them into one of the documentation fields available
for each variable.

Bob McConnaughey
Westat/NIEHS Epidemiology Support.

"At times like this, an adult needs a drink."
Dance, Dance, Dance.  H. Murakami
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