Hi,
I have a dataset that contains four choice tasks for each individual, with five alternatives for each task and four different attributes. Additionally, I have four other variables that are constant for each person (gender, income, age, area). As shown below, part of my dataset is displayed.
I am seeking a Latent Class MNL model with a reference category (alternative B). In addition to the table comparing the coefficients for each alternative, I need to know which class each person belongs to. I would appreciate your advice.
I have a dataset that contains four choice tasks for each individual, with five alternatives for each task and four different attributes. Additionally, I have four other variables that are constant for each person (gender, income, age, area). As shown below, part of my dataset is displayed.
I am seeking a Latent Class MNL model with a reference category (alternative B). In addition to the table comparing the coefficients for each alternative, I need to know which class each person belongs to. I would appreciate your advice.
ID | Choicetask | Alternative | Choice | Attribute 1 | Attribute 2 | Attribute 3 | Attribute 4 | Female | Age | Income | Area |
1 | 1 | A | 1 | 72 | 300 | 1 | 0 | 0 | 23 | 13 | 5 |
1 | 1 | B | 0 | 168 | 280 | 1 | 1 | 0 | 23 | 13 | 5 |
1 | 1 | C | 0 | 36 | 900 | 1 | 1 | 0 | 23 | 13 | 5 |
1 | 1 | D | 0 | 144 | 480 | 0 | 0 | 0 | 23 | 13 | 5 |
1 | 1 | E | 0 | 70 | 840 | 1 | 0 | 0 | 23 | 13 | 5 |
1 | 2 | A | 0 | 108 | 525 | 0 | 1 | 0 | 23 | 13 | 5 |
1 | 2 | B | 1 | 120 | 240 | 0 | 0 | 0 | 23 | 13 | 5 |
1 | 2 | C | 0 | 54 | 900 | 1 | 1 | 0 | 23 | 13 | 5 |
1 | 2 | D | 0 | 120 | 320 | 0 | 1 | 0 | 23 | 13 | 5 |
1 | 2 | E | 0 | 56 | 600 | 0 | 0 | 0 | 23 | 13 | 5 |
1 | 3 | A | 0 | 90 | 525 | 0 | 0 | 0 | 23 | 13 | 5 |
1 | 3 | B | 1 | 96 | 200 | 1 | 0 | 0 | 23 | 13 | 5 |
1 | 3 | C | 0 | 63 | 600 | 0 | 1 | 0 | 23 | 13 | 5 |
1 | 3 | D | 0 | 120 | 560 | 0 | 0 | 0 | 23 | 13 | 5 |
1 | 3 | E | 0 | 70 | 720 | 0 | 0 | 0 | 23 | 13 | 5 |
1 | 4 | A | 0 | 90 | 450 | 1 | 1 | 0 | 23 | 13 | 5 |
1 | 4 | B | 1 | 144 | 160 | 0 | 1 | 0 | 23 | 13 | 5 |
1 | 4 | C | 0 | 45 | 900 | 0 | 1 | 0 | 23 | 13 | 5 |
1 | 4 | D | 0 | 96 | 560 | 0 | 1 | 0 | 23 | 13 | 5 |
1 | 4 | E | 0 | 84 | 720 | 1 | 0 | 0 | 23 | 13 | 5 |
2 | 1 | A | 0 | 72 | 525 | 0 | 0 | 1 | 61 | 40 | 5.5 |
2 | 1 | B | 0 | 120 | 280 | 0 | 1 | 1 | 61 | 40 | 5.5 |
2 | 1 | C | 1 | 63 | 600 | 1 | 1 | 1 | 61 | 40 | 5.5 |
2 | 1 | D | 0 | 144 | 400 | 1 | 1 | 1 | 61 | 40 | 5.5 |
2 | 1 | E | 0 | 70 | 720 | 1 | 1 | 1 | 61 | 40 | 5.5 |
2 | 2 | A | 1 | 90 | 375 | 0 | 1 | 1 | 61 | 40 | 5.5 |
2 | 2 | B | 0 | 168 | 280 | 0 | 0 | 1 | 61 | 40 | 5.5 |
2 | 2 | C | 0 | 36 | 1050 | 0 | 0 | 1 | 61 | 40 | 5.5 |
2 | 2 | D | 0 | 168 | 560 | 0 | 1 | 1 | 61 | 40 | 5.5 |
2 | 2 | E | 0 | 56 | 720 | 1 | 1 | 1 | 61 | 40 | 5.5 |
2 | 3 | A | 0 | 72 | 450 | 0 | 1 | 1 | 61 | 40 | 5.5 |
2 | 3 | B | 0 | 144 | 280 | 1 | 0 | 1 | 61 | 40 | 5.5 |
2 | 3 | C | 0 | 54 | 1050 | 0 | 1 | 1 | 61 | 40 | 5.5 |
2 | 3 | D | 0 | 144 | 320 | 1 | 1 | 1 | 61 | 40 | 5.5 |
2 | 3 | E | 1 | 70 | 480 | 0 | 1 | 1 | 61 | 40 | 5.5 |
2 | 4 | A | 0 | 90 | 300 | 1 | 0 | 1 | 61 | 40 | 5.5 |
2 | 4 | B | 1 | 120 | 240 | 1 | 1 | 1 | 61 | 40 | 5.5 |
2 | 4 | C | 0 | 54 | 750 | 0 | 0 | 1 | 61 | 40 | 5.5 |
2 | 4 | D | 0 | 144 | 560 | 0 | 0 | 1 | 61 | 40 | 5.5 |
2 | 4 | E | 0 | 98 | 720 | 0 | 1 | 1 | 61 | 40 | 5.5 |