Stata 15 help for cnreg

help cnreg dialogs: cnreg svy: cnreg also see: cnreg postestimation previously documented ------------------------------------------------------------------------------- cnreg continues to work but, as of Stata 11, is no longer an official part of Stata. This is the original help file, which we will no longer update, so some links may no longer work.

See intreg for a recommended alternative to cnreg.


[R] cnreg -- Censored-normal regression


cnreg depvar [indepvars] [if] [in] [weight] , censored(varname) [options]

options Description ------------------------------------------------------------------------- Model * censored(varname) variable indicating whether depvar is not censored (0), left censored (-1), or right censored (1) 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)

Max options maximize_options control the maximization process; seldom used ------------------------------------------------------------------------- * censored(varname) is required. bootstrap, by, jackknife, nestreg, rolling, statsby, stepwise, svy, and xi 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] cnreg postestimation for features available after estimation.


cnreg fits a model of depvar on indepvars, where depvar contains both observations and censored observations on the process. Censoring values may vary from observation to observation.


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

censored(varname) is required. varname is a variable indicating if depvar is censored and, if so, whether the censoring is left or right. 0 indicates that depvar is not censored. -1 indicates left censoring; the true value is known only to be less than or equal to the value recorded in depvar. +1 indicates right censoring; the true value is known only to be greater than or equal to the value recorded in depvar.

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, opg), 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.

+-------------+ ----+ Max options +------------------------------------------------------

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

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


Setup . webuse news2

Perform censored-normal regression . cnreg date lncltn famown, censored(cnsrd)

Replay results, using 99% CI . cnreg, level(99)

Saved results

cnreg 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(ll) log likelihood e(ll_0) log likelihood, constant-only model e(N_clust) number of clusters e(chi2) chi-squared statistic e(p) p-value for chi-squared test e(converged) 1 if converged, 0 otherwise

Macros e(cmd) cnreg e(cmdline) command as typed e(depvar) name of dependent variable e(censored) variable specified in censored() 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) Wald or 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

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

Functions e(sample) marks estimation sample

Also see

Manual: previously documented

Help: [R] cnreg postestimation; [R] intreg, [R] regress, [R] tobit, [SVY] svy estimation, [XT] xtintreg, [XT] xttobit

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