Hello,

I wanted to ask if anyone knows how to implement the mixlogit command when you have proportions. In my example, y represents the proportion of individuals picking item 1 a time 1. 1-y is the proportion of individuals who did not pick item 1.

Next, I've followed the advice of the 2nd post here: https://www.statalist.org/forums/for...n-rating-scale

But all variants of mixlogit don't work for me such as: mixlogit dep k [pw=y], group(id) rand(x1)

In the above case, I get an error saying : weights must be the same for all observations in a group. Since all id's will have different y's, does anyone know how I can implement the command with my data?

Many thanks!


Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input float(id y k x1 t) long newid float(n dep)
 1  .002072341  4.874727 4.62 1  1 1 1
 1    .9979277  4.874727 4.62 1  2 2 0
 2 .0037607455  5.384451 4.46 1  3 1 1
 2    .9962392  5.384451 4.46 1  4 2 0
 3  .006420378  3.514521 4.76 1  5 1 1
 3    .9935796  3.514521 4.76 1  6 2 0
 4 .0030985705  6.375185 5.06 1  7 1 1
 4    .9969015  6.375185 5.06 1  8 2 0
 5  .004318112  3.737104  5.2 1  9 1 1
 5    .9956819  3.737104  5.2 1 10 2 0
 6   .00248359 3.7184365   .2 1 11 1 1
 6    .9975164 3.7184365   .2 1 12 2 0
 7  .008919741  3.679313 3.99 1 13 1 1
 7    .9910803  3.679313 3.99 1 14 2 0
 8  .002419378  4.843454 5.06 1 15 1 1
 8    .9975806  4.843454 5.06 1 16 2 0
 9  .004127612  5.683865 5.22 1 17 1 1
 9    .9958724  5.683865 5.22 1 18 2 0
10 .0023773876  6.376777 4.11 1 19 1 1
10    .9976226  6.376777 4.11 1 20 2 0
11  .002161125   6.53898 4.11 2 21 1 1
11    .9978389   6.53898 4.11 2 22 2 0
12  .004792569  3.383333   .2 2 23 1 1
12    .9952074  3.383333   .2 2 24 2 0
13 .0017331602  4.877793 5.06 2 25 1 1
13    .9982668  4.877793 5.06 2 26 2 0
14 .0025436045   5.78125 4.46 2 27 1 1
14    .9974564   5.78125 4.46 2 28 2 0
15  .004611214  5.543891 5.22 2 29 1 1
15    .9953888  5.543891 5.22 2 30 2 0
16  .004510679  5.595192 5.06 2 31 1 1
16    .9954893  5.595192 5.06 2 32 2 0
17  .009309353  3.679394 3.99 2 33 1 1
17    .9906906  3.679394 3.99 2 34 2 0
18 .0046460396  3.860588  5.2 2 35 1 1
18    .9953539  3.860588  5.2 2 36 2 0
19  .007048203      3.59 4.76 2 37 1 1
19    .9929518      3.59 4.76 2 38 2 0
20 .0018098027  4.966027 4.62 2 39 1 1
20    .9981902  4.966027 4.62 2 40 2 0
21 .0021115127   4.88726 4.62 3 41 1 1
21    .9978885   4.88726 4.62 3 42 2 0
22  .002664701      6.19 5.06 3 43 1 1
22    .9973353      6.19 5.06 3 44 2 0
23   .00199405      5.79 4.46 3 45 1 1
23    .9980059      5.79 4.46 3 46 2 0
24 .0029257545  5.869352 5.22 3 47 1 1
24    .9970742  5.869352 5.22 3 48 2 0
25 .0009679417      5.49 5.06 3 49 1 1
25    .9990321      5.49 5.06 3 50 2 0
end