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From |
Michael E Roettger <meroett@bgsu.edu> |

To |
"statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu> |

Subject |
st: Problem interpreting results from xttobit |

Date |
Fri, 10 Oct 2008 09:58:23 -0400 |

Dear STATA list, I am trying to determine if my (i) regression results are valid using xttobit and (ii) how to interpret my results due to a major shift in likelihood functions. I have been using a random effects tobit model to a measure left-censored variable [a propensity to commit delinquent acts among a panel of respondents]. My initial model provides negative log-likehood with an individual-level random effect that seems reasonable: >Random-effects tobit regression Number of obs = 2401 >Group variable: aid Number of groups = 804 >Random effects u_i ~ Gaussian Obs per group: min = 2 > avg = 3.0 > max = 3 > Wald chi2(3) = 91.53 >Log likelihood = -4211.3782 Prob > chi2 = 0.0000 . . . > /sigma_u | 2.079586 .2733142 7.61 0.000 1.5439 2.615272 > /sigma_e | 5.835778 .1588994 36.73 0.000 5.524341 6.147215 >-------------+---------------------------------------------------------------- > rho | .1126776 .0284796 .0662654 .1786233 >------------------------------------------------------------------------------ However, after adding several variables, the log-likelihood becomes highly positive and the individual-level random effect that is of the order of E-39 >Random-effects tobit regression Number of obs = 2294 >Group variable: aid Number of groups = 768 > >Random effects u_i ~ Gaussian Obs per group: min = 2 > avg = 3.0 > max = 3 > > Wald chi2(9) = 300.30 >Log likelihood = 52807.689 Prob > chi2 = 0.0000 . . . > /sigma_u | 4.17e-39 1.06e-40 39.19 0.000 3.96e-39 4.38e-39 > /sigma_e | 5.793114 .140685 41.18 0.000 5.517377 6.068852 >-------------+---------------------------------------------------------------- > rho | 5.19e-79 3.65e-80 4.52e-79 5.95e-79 >------------------------------------------------------------------------------ Both models converge to a concave solution and I am estimating about 35 quadrature points for the Gauss-Hermite function. Other than the random effects, the estimated coefficients for Beta's are consistent with theory/prior research. Its just the change in likelihood and a highly significant random effect near zero from the first to the second models above that leave me scratching my head. Thanks for your time and help! Mike Roettger * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: Problem interpreting results from xttobit***From:*"Rodrigo Alfaro A." <ralfaro@bcentral.cl>

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