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  • mixlogitwtp: Variable has no within-group variance

    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):
    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

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