help tobit dialogs: tobit svy: tobit
also see: tobit postestimation
-------------------------------------------------------------------------------
Title
[R] tobit -- Tobit regression
Syntax
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 spacing and display of omitted variables
and base and empty cells
Maximization
maximize_options control the maximization process; seldom used
+ coeflegend display coefficients' legend instead of coefficient
table
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* You must specify at least one of ll[(#)] or ul[(#)].
+ coeflegend does not appear in the dialog box.
indepvars may contain factor variables; see fvvarlist.
bootstrap, by, 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, pweights, and iweights are allowed; see weight.
See [R] tobit postestimation for features available after estimation.
Menu
Statistics > Linear models and related > Censored regression > Tobit
regression
Description
tobit fits a model of depvar on indepvars where the censoring values are
fixed.
Options
+-------+
----+ 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, that are
robust to some kinds of misspecification, that allow for intragroup
correlation, and that use bootstrap or jackknife methods; see [R]
vce_option.
+-----------+
----+ Reporting +--------------------------------------------------------
level(#); see [R] estimation options.
display_options: noomitted, vsquish, noemptycells, baselevels,
allbaselevels; see [R] estimation options.
+--------------+
----+ Maximization +-----------------------------------------------------
maximize_options: iterate(#), [no]log, trace, tolerance(#),
ltolerance(#), nrtolerance(#), 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.
Examples
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Setup
. sysuse auto
. generate wgt=weight/1000
Censored from below
. tobit mpg wgt, ll(17)
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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)
---------------------------------------------------------------------------
Saved results
tobit saves 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) offset
e(chi2type) LR; type of model chi-squared test
e(vce) vcetype specified in vce()
e(vcetype) title used to label Std. Err.
e(crittype) optimization criterion
e(properties) b V
e(predict) program used to implement predict
e(footnote) program used to implement the footnote display
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
Also see
Manual: [R] tobit
Help: [R] tobit postestimation;
[R] intreg, [R] heckman, [R] ivtobit, [R] regress, [R] truncreg,
> [XT] xtintreg, [XT] xttobit
