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Re: data mismatches [message #3525 is a reply to message #3352] Fri, 26 December 2014 03:57 Go to previous messageGo to previous message
jinexoxo is currently offline  jinexoxo
Messages: 22
Registered: October 2014
Location: Laguna, Philippines
Member

Hi. Good day, sir!

I am now in the middle of an analysis. I thank you so much for always accommodating and answering all my questions.

I have another problem with my study.

I generated "wife experience physical violence for the last 12 mos" with this:gen victim = (inlist(d105a, 1, 2, 4) | inlist(d105b, 1, 2, 4) | inlist(d105c, 1, 2, 4) | inlist(d105d, 1, 2, 4) | inlist(d105e, 1, 2, 4) | inlist(d105f, 1, 2, 4) | inlist(d105g, 1, 2, 4) | inlist(d105j, 1, 2, 4)) if v502 >0 I recoded 0 as No and 1 as Yes.

Next, I drop some unnecessary observations: drop if v502 == 0

I tried to run a logistic regression with a single independent variable and I got this:

. [i]logistic victim v012 if v024 == 1 [iw=d005/1000000][/i]

Logistic regression Number of obs = 942
LR chi2(1) = 15.23
Prob > chi2 = 0.0001
Log likelihood = -215.9921 Pseudo R2 = 0.0341

------------------------------------------------------------ ------------------
victim | Odds Ratio Std. Err. z P>|z| [95% Conf. Interval]
-------------+---------------------------------------------- ------------------
v012 | .9359899 .0163611 -3.78 0.000 .9044659 .9686127
_cons | .435881 .2389604 -1.51 0.130 .1488397 1.276489
------------------------------------------------------------ ------------------

Question: Why do I always get 942 observations when I actually used weights in the data? I expected that the number of observations would be 1144.

Again, thank you ... and merry Xmas! :)


J. Amora
 
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