Hi,
I have a dataset like the example below (except that I have 14 variables achado*_mlc and not just 3, and 101 obserb) in which 'olho' is the identifying variable .
What I am struggling to do is to find a way to discover the combination of any of these 14 'achado*_mlc' variables - all dichotomous, that better predicts 'chave' having as 'PCV' as answer (chave is also dichotomous). I would really appreciate some suggestions and how to implement them on Stata. I am using Stata 13.0 for Win 64-bit.
Thank you in advance for your help.
Best
Miguel
dataset example:
Sorry for the very poor formatting. I tried to fix it. unsuccessfully
I have a dataset like the example below (except that I have 14 variables achado*_mlc and not just 3, and 101 obserb) in which 'olho' is the identifying variable .
What I am struggling to do is to find a way to discover the combination of any of these 14 'achado*_mlc' variables - all dichotomous, that better predicts 'chave' having as 'PCV' as answer (chave is also dichotomous). I would really appreciate some suggestions and how to implement them on Stata. I am using Stata 13.0 for Win 64-bit.
Thank you in advance for your help.
Best
Miguel
dataset example:
olho | achado1_mlc | achado3_mlc | achado5_mlc | chave |
1 | 1 | 1 | 1 | PCV |
2 | 0 | 0 | 0 | No PCV |
3 | 0 | 0 | 0 | No PCV |
4 | 1 | 1 | 1 | PCV |
5 | 1 | 1 | 1 | PCV |
6 | 1 | 1 | 1 | PCV |
7 | 0 | 0 | 0 | No PCV |
8 | 0 | 0 | 0 | No PCV |
9 | 0 | 0 | 0 | No PCV |
10 | 1 | 1 | 0 | PCV |
11 | 0 | 0 | 0 | No PCV |
12 | 1 | 0 | 1 | PCV |
13 | 1 | 1 | 0 | No PCV |
14 | 1 | 1 | 1 | PCV |
15 | 0 | 0 | 0 | No PCV |
16 | 1 | 0 | 0 | PCV |
17 | 0 | 0 | 0 | No PCV |
18 | 0 | 0 | 0 | No PCV |
19 | 0 | 0 | 0 | No PCV |
20 | 0 | 0 | 1 | PCV |
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