Cy wrote:
In a previous post, I indicated there was a drastic reduction in my
sub-population size. I traced the problem to a variable with a lot of
missing cases.
As you can see from the table below, this variable elicits whether the
respondent engaged in unprotected sexual intercourse. About a third of
the cases (33.78%) are missing.
V761 -- Last intercourse used condom
-----------------------------------------------------------
| Freq. Percent Valid Cum.
---------------+--------------------------------------------
Valid 0 No | 6012 56.16 84.81 84.81
1 Yes | 1075 10.04 15.16 99.97
9 | 2 0.02 0.03 100.00
Total | 7089 66.22 100.00
Missing . | 3617 33.78
Total | 10706 100.00
-----------------------------------------------------------
Since the dependent variable in my deals with HIV risk, I need to
include sexual risk variables such as the V761 in the model. How do I
deal with this missing data problem, so that it does not affect my
sample size. Would an imputation work?
==========================================================
In this case, I would avoid imputation and instead generate two dummy
variables:
V761_0 = 1 if no condom use, otherwise 0
V761_miss = 1 if missing or 9, otherwise 0
. generate V761_0 = V761==0
. generate V761_miss = V761>1
. groups V761* , missing
+--------------------------------------------+
| V761 V761_0 V761_m~s Freq. Percent |
|--------------------------------------------|
| 0 1 0 6012 56.16 |
| 1 0 0 1075 10.04 |
| 9 0 1 2 0.02 |
| . 0 1 3617 33.78 |
+--------------------------------------------+
-groups- is an unofficial command (ssc install groups).
Both variables should be included in your regression. You will still
have a problem interpreting what missing means, but that problem
can not be solved by imputation.
Hope this helps
Svend
________________________________________________________
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(School of Public Health, Department of Epidemiology)
Bartholins Allé 2
DK-8000 Aarhus C, Denmark
Phone: +45 8693 7796
Mobile: +45 2634 7796
E-mail: [email protected]
_________________________________________________________
