I have estimated my discrete choice experiment with 'mixlogitwtp' and it ran perfectly:
. mixlogitwtp choice rec_some rec_all eh_high wq_inc ei_pos, group(setid) price(mtax)
Iteration 0: log likelihood = -10467.376
Iteration 1: log likelihood = -10466.948
Iteration 2: log likelihood = -10466.703
Iteration 3: log likelihood = -10466.689
Iteration 4: log likelihood = -10466.688
Mixed logit model in WTP space Number of obs = 29,220
Wald chi2(6) = 3667.42
Log likelihood = -10466.688 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
choice | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Mean |
rec_some | 27.50139 7.621863 3.61 0.000 12.56281 42.43996
rec_all | 85.18586 8.760342 9.72 0.000 68.0159 102.3558
eh_high | 76.64796 8.281869 9.25 0.000 60.4158 92.88013
wq_inc | 92.22739 9.187993 10.04 0.000 74.21926 110.2355
ei_pos | 139.1418 10.5668 13.17 0.000 118.4312 159.8523
mtax | -5.639376 .0974011 -57.90 0.000 -5.830279 -5.448474
-------------+----------------------------------------------------------------
SD |
mtax | -.3066658 .2728991 -1.12 0.261 -.8415383 .2282067
------------------------------------------------------------------------------
The sign of the estimated standard deviations is irrelevant: interpret them as
being positive
When I am including my demographic variables that are dummy coded (0/1) I receive this error for every single variable: Variable 'x' has no within-group variance
Here is an example of my dataset (there are 27,000 observations):
. mixlogitwtp choice rec_some rec_all eh_high wq_inc ei_pos, group(setid) price(mtax)
Iteration 0: log likelihood = -10467.376
Iteration 1: log likelihood = -10466.948
Iteration 2: log likelihood = -10466.703
Iteration 3: log likelihood = -10466.689
Iteration 4: log likelihood = -10466.688
Mixed logit model in WTP space Number of obs = 29,220
Wald chi2(6) = 3667.42
Log likelihood = -10466.688 Prob > chi2 = 0.0000
------------------------------------------------------------------------------
choice | Coef. Std. Err. z P>|z| [95% Conf. Interval]
-------------+----------------------------------------------------------------
Mean |
rec_some | 27.50139 7.621863 3.61 0.000 12.56281 42.43996
rec_all | 85.18586 8.760342 9.72 0.000 68.0159 102.3558
eh_high | 76.64796 8.281869 9.25 0.000 60.4158 92.88013
wq_inc | 92.22739 9.187993 10.04 0.000 74.21926 110.2355
ei_pos | 139.1418 10.5668 13.17 0.000 118.4312 159.8523
mtax | -5.639376 .0974011 -57.90 0.000 -5.830279 -5.448474
-------------+----------------------------------------------------------------
SD |
mtax | -.3066658 .2728991 -1.12 0.261 -.8415383 .2282067
------------------------------------------------------------------------------
The sign of the estimated standard deviations is irrelevant: interpret them as
being positive
When I am including my demographic variables that are dummy coded (0/1) I receive this error for every single variable: Variable 'x' has no within-group variance
Here is an example of my dataset (there are 27,000 observations):
id | choiceset | block | alt | optionA | optionB | optionC | choice | tax | Rec_None | Rec_Some | Rec_All | EH_High | EH_Low | WQ_Inc | WQ_Dec | EI_Pos | EI_Neg | setid | Gender.Female | Age | Resident.FL | Income20 | income40 | income60 | income80 | income100 | income100P | Race | White | African.Am | Hispanic | AI | Asian.Am | NH |
1 | 1 | 3 | 1 | 1 | 0 | 0 | 0 | 100 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 1 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 1 | 3 | 2 | 0 | 1 | 0 | 1 | 150 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 1 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 2 | 3 | 1 | 1 | 0 | 0 | 1 | 100 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 2 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 2 | 3 | 2 | 0 | 1 | 0 | 0 | 50 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 2 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 2 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 3 | 3 | 1 | 1 | 0 | 0 | 0 | 200 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 3 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 3 | 3 | 2 | 0 | 1 | 0 | 0 | 100 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 3 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 3 | 3 | 3 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 4 | 3 | 1 | 1 | 0 | 0 | 0 | 150 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 4 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 4 | 3 | 2 | 0 | 1 | 0 | 0 | 200 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 4 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
1 | 4 | 3 | 3 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0 | 31 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0 | 0 |
2 | 1 | 3 | 1 | 1 | 0 | 0 | 0 | 100 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 5 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 1 | 3 | 2 | 0 | 1 | 0 | 1 | 150 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 5 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 1 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 2 | 3 | 1 | 1 | 0 | 0 | 1 | 100 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 6 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 2 | 3 | 2 | 0 | 1 | 0 | 0 | 50 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 6 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 2 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 3 | 3 | 1 | 1 | 0 | 0 | 1 | 200 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 7 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 3 | 3 | 2 | 0 | 1 | 0 | 0 | 100 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 7 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 3 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 4 | 3 | 1 | 1 | 0 | 0 | 0 | 150 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 8 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 4 | 3 | 2 | 0 | 1 | 0 | 1 | 200 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 8 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
2 | 4 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 | 1 | 39 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 1 | 3 | 1 | 1 | 0 | 0 | 0 | 100 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 9 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 1 | 3 | 2 | 0 | 1 | 0 | 1 | 150 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 9 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 1 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 2 | 3 | 1 | 1 | 0 | 0 | 0 | 100 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 10 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 2 | 3 | 2 | 0 | 1 | 0 | 1 | 50 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 10 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 2 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 3 | 3 | 1 | 1 | 0 | 0 | 0 | 200 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 11 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 3 | 3 | 2 | 0 | 1 | 0 | 1 | 100 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 | 11 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 3 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 4 | 3 | 1 | 1 | 0 | 0 | 1 | 150 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 12 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 4 | 3 | 2 | 0 | 1 | 0 | 0 | 200 | 1 | 0 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 12 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |
3 | 4 | 3 | 3 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 1 | 44 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |