Stata 15 help for tobit_14


[R] tobit -- Tobit regression (syntax prior to version 15)

[The tobit command was improved as of version 15. This help file documents tobit's old behavior and as such is probably of no interest to you. Click here for the help file of the current tobit command.]


tobit depvar [indepvars] [if] [in] [weight] , ll[(#)] ul[(#)] [options]

options Description ------------------------------------------------------------------------- Model noconstant suppress constant term * ll[(#)] left-censoring limit * ul[(#)] right-censoring limit offset(varname) include varname in model with coefficient constrained to 1

SE/Robust vce(vcetype) vcetype may be oim, robust, cluster clustvar, bootstrap, or jackknife

Reporting level(#) set confidence level; default is level(95) display_options control columns and column formats, row spacing, line width, display of omitted variables and base and empty cells, and factor-variable labeling

Maximization maximize_options control the maximization process; seldom used

coeflegend display legend instead of statistics ------------------------------------------------------------------------- * You must specify at least one of ll[(#)] or ul[(#)]. indepvars may contain factor variables; see fvvarlist. depvar and indepvars may contain time-series operators; see tsvarlist. bootstrap, by, fp, jackknife, nestreg, rolling, statsby, stepwise, and svy are allowed; see prefix. Weights are not allowed with the bootstrap prefix. aweights are not allowed with the jackknife prefix. vce() and weights are not allowed with the svy prefix. aweights, fweights, iweights, and pweights are allowed; see weight. coeflegend does not appear in the dialog box. See [R] tobit postestimation for features available after estimation.


Statistics > Linear models and related > Censored regression > Tobit regression


tobit fits a model of depvar on indepvars where the censoring values are fixed.


+-------+ ----+ Model +------------------------------------------------------------

noconstant; see [R] estimation options.

ll[(#)] and ul[(#)] indicate the lower and upper limits for censoring, respectively. You may specify one or both. Observations with depvar <= ll() are left-censored; observations with depvar >= ul() are right-censored; and remaining observations are not censored. You do not have to specify the censoring value at all. It is enough to type ll, ul, or both. When you do not specify a censoring value, tobit assumes that the lower limit is the minimum observed in the data (if ll is specified) and the upper limit is the maximum (if ul is specified) .

offset(varname); see [R] estimation options.

+-----------+ ----+ SE/Robust +--------------------------------------------------------

vce(vcetype) specifies the type of standard error reported, which includes types that are derived from asymptotic theory (oim), that are robust to some kinds of misspecification (robust), that allow for intragroup correlation (cluster clustvar), and that use bootstrap or jackknife methods (bootstrap, jackknife); see [R] vce_option.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#); see [R] estimation options.

display_options: noci, nopvalues, noomitted, vsquish, noemptycells, baselevels, allbaselevels, nofvlabel, fvwrap(#), fvwrapon(style), cformat(%fmt), pformat(%fmt), sformat(%fmt), and nolstretch; see [R] estimation options.

+--------------+ ----+ Maximization +-----------------------------------------------------

maximize_options: iterate(#), [no]log, trace, tolerance(#), ltolerance(#), nrtolerance(#), and nonrtolerance; see [R] maximize. These options are seldom used.

Unlike most maximum likelihood commands, tobit defaults to nolog -- it suppresses the iteration log.

The following option is available with tobit but is not shown in the dialog box:

coeflegend; see [R] estimation options.


--------------------------------------------------------------------------- Setup . sysuse auto . generate wgt=weight/1000

Censored from below . tobit mpg wgt, ll(17)

--------------------------------------------------------------------------- Setup . sysuse auto, clear . generate wgt=weight/100

Censored from above . tobit mpg wgt, ul(24)

Clustered on foreign . tobit mpg wgt, ul(24) vce(cluster foreign)

Two-limit tobit . tobit mpg wgt, ll(17) ul(24) ---------------------------------------------------------------------------

Stored results

tobit stores the following in e():

Scalars e(N) number of observations e(N_unc) number of uncensored observations e(N_lc) number of left-censored observations e(N_rc) number of right-censored observations e(llopt) contents of ll(), if specified e(ulopt) contents of ul(), if specified e(k_aux) number of auxiliary parameters e(df_m) model degrees of freedom e(df_r) residual degrees of freedom e(r2_p) pseudo-R-squared e(chi2) chi-squared e(ll) log likelihood e(ll_0) log likelihood, constant-only model

e(N_clust) number of clusters e(F) F statistic e(p) significance e(rank) rank of e(V) e(converged) 1 if converged, 0 otherwise

Macros e(cmd) tobit e(cmdline) command as typed e(depvar) name of dependent variable e(wtype) weight type e(wexp) weight expression e(title) title in estimation output e(clustvar) name of cluster variable e(offset) linear offset variable e(chi2type) LR; type of model chi-squared test e(vce) vcetype specified in vce() e(vcetype) title used to label Std. Err. e(properties) b V e(predict) program used to implement predict e(footnote) program and arguments to display footnote e(marginsok) predictions allowed by margins e(asbalanced) factor variables fvset as asbalanced e(asobserved) factor variables fvset as asobserved

Matrices e(b) coefficient vector e(V) variance-covariance matrix of the estimators e(V_modelbased) model-based variance

Functions e(sample) marks estimation sample

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