Todd wrote:
For an HIV programme in Benin we had 59 persons lost to follow-up.
We were able to do home visits for 41 persons, after which 33
returned to clinical care. Of those 18 we were not able to visit,
only 8 returned to clinical care.
What is the most efficient way to create a mini database to define
the odds ratio...the odds of returning for clinical care after a
home visit as compared to those not visited. I could simply go
into the Data Editor of a blank database and enter the numbers...
but Id like to type in the data.
Visited 41 (33 reintegrated)
Not Visited 18 (8 reintegrated)
Total 59
----------------------------------------------------
Michael and Sebastian gave valid suggestions. But since you ask for
odds ratios, the most direct way is -cci- :
. cci 33 8 8 10
Proportion
| Exposed Unexposed | Total Exposed
-----------------+------------------------+------------------------
Cases | 33 8 | 41 0.8049
Controls | 8 10 | 18 0.4444
-----------------+------------------------+------------------------
Total | 41 18 | 59 0.6949
| |
| Point estimate | [95% Conf. Interval]
|------------------------+------------------------
Odds ratio | 5.15625 | 1.311065 20.46528 (exact)
Attr. frac. ex. | .8060606 | .2372611 .9511368 (exact)
Attr. frac. pop | .6487805 |
+-------------------------------------------------
chi2(1) = 7.66 Pr>chi2 = 0.0056
You could also create your "database" with the -input- command_
clear
input visit reint n
0 0 10
0 1 8
1 0 8
1 1 33
end
and use -n- as frequency weight:
cc reint visit [fweight=n]
or -expand- the dataset:
expand n
cc reint visit
Hope this helps
Svend
________________________________________________________
Svend Juul
Institut for Folkesundhed, Afdeling for Epidemiologi
(Institute of Public Health, Department of Epidemiology)
Vennelyst Boulevard 6
DK-8000 Aarhus C, Denmark
Phone, work: +45 8942 6090
Phone, home: +45 8693 7796
Fax: +45 8613 1580
E-mail: [email protected]
_________________________________________________________
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