Stata 15 help for teffects ra

[TE] teffects ra -- Regression adjustment

Syntax

teffects ra (ovar omvarlist [, omodel noconstant]) (tvar) [if] [in] [weight] [, stat options]

ovar is a binary, count, continuous, fractional, or nonnegative outcome of interest.

omvarlist specifies the covariates in the outcome model.

tvar must contain integer values representing the treatment levels.

omodel Description ------------------------------------------------------------------------- Model linear linear outcome model; the default logit logistic outcome model probit probit outcome model hetprobit(varlist) heteroskedastic probit outcome model poisson exponential outcome model flogit fractional logistic outcome model fprobit fractional probit outcome model fhetprobit(varlist) fractional heteroskedastic probit outcome model ------------------------------------------------------------------------- omodel specifies the model for the outcome variable.

stat Description ------------------------------------------------------------------------- Stat ate estimate average treatment effect in population; the default atet estimate average treatment effect on the treated pomeans estimate potential-outcome means -------------------------------------------------------------------------

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

Reporting level(#) set confidence level; default is level(95) aequations display auxiliary-equation results 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

Advanced control(# | label) specify the level of tvar that is the control tlevel(# | label) specify the level of tvar that is the treatment

coeflegend display legend instead of statistics -------------------------------------------------------------------------

omvarlist may contain factor variables; see fvvarlists. bootstrap, by, jackknife, and statsby are allowed; see prefix. Weights are not allowed with the bootstrap prefix. fweights, iweights, and pweights are allowed; see weight. coeflegend does not appear in the dialog box. See [TE] teffects postestimation for features available after estimation.

Menu

Statistics > Treatment effects > Continuous outcomes > Regression adjustment

Statistics > Treatment effects > Binary outcomes > Regression adjustment

Statistics > Treatment effects > Count outcomes > Regression adjustment

Statistics > Treatment effects > Fractional outcomes > Regression adjustment

Statistics > Treatment effects > Nonnegative outcomes > Regression adjustment

Description

teffects ra estimates the average treatment effect, the average treatment effect on the treated, and the potential-outcome means from observational data by regression adjustment. Regression adjustment estimators use contrasts of averages of treatment-specific predicted outcomes to estimate treatment effects. teffects ra accepts a continuous, binary, count, fractional, or nonnegative outcome and allows a multivalued treatment.

See [TE] teffects intro or [TE] teffects intro advanced for more information about estimating treatment effects from observational data.

Options

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

noconstant; see [R] estimation options.

+------+ ----+ Stat +-------------------------------------------------------------

stat is one of three statistics: ate, atet, or pomeans. ate is the default.

ate specifies that the average treatment effect be estimated.

atet specifies that the average treatment effect on the treated be estimated.

pomeans specifies that the potential-outcome means for each treatment level be estimated.

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

vce(vcetype) specifies the type of standard error reported, which includes types 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.

aequations specifies that the results for the outcome-model or the treatment-model parameters be displayed. By default, the results for these auxiliary parameters are not displayed.

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, and from(init_specs); see [R] maximize. These options are seldom used.

init_specs is one of

matname [, skip copy]

# [, # ...], copy

+----------+ ----+ Advanced +---------------------------------------------------------

control(# | label) specifies the level of tvar that is the control. The default is the first treatment level. You may specify the numeric level # (a nonnegative integer) or the label associated with the numeric level. control() may not be specified with statistic pomeans. control() and tlevel() may not specify the same treatment level.

tlevel(# | label) specifies the level of tvar that is the treatment for the statistic atet. The default is the second treatment level. You may specify the numeric level # (a nonnegative integer) or the label associated with the numeric level. tlevel() may only be specified with statistic atet. tlevel() and control() may not specify the same treatment level.

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

coeflegend; see [R] estimation options.

Examples

Setup . webuse cattaneo2

Estimate the average treatment effect of smoking, controlling for first-trimester exam status, marital status, mother's age, and first-birth status . teffects ra (bweight prenatal1 mmarried mage fbaby) (mbsmoke)

Refit the above model, but obtain the average treatment effects on the treated rather than the average treatment effect . teffects ra (bweight prenatal1 mmarried mage fbaby) (mbsmoke), atet

Refit the above model, but display the POMs and the estimated regression coefficients for the treated and untreated subjects . teffects ra (bweight prenatal1 mmarried mage fbaby) (mbsmoke), pomeans aequations

Video example

Treatment effects: Regression adjustment

Stored results

teffects ra stores the following in e():

Scalars e(N) number of observations e(nj) number of observations for treatment level j e(N_clust) number of clusters e(k_eq) number of equations in e(b) e(k_levels) number of levels in treatment variable e(treated) level of treatment variable defined as treated e(control) level of treatment variable defined as control e(converged) 1 if converged, 0 otherwise

Macros e(cmd) teffects e(cmdline) command as typed e(depvar) name of outcome variable e(tvar) name of treatment variable e(subcmd) ra e(omodel) linear, logit, probit, hetprobit, poisson, flogit, fprobit, or fhetprobit e(stat) statistic estimated, ate, atet, or pomeans e(wtype) weight type e(wexp) weight expression e(title) title in estimation output e(clustvar) name of cluster variable e(tlevels) levels of treatment variable e(vce) vcetype specified in vce() e(vcetype) title used to label Std. Err. e(properties) b V e(estat_cmd) program used to implement estat e(predict) program used to implement predict e(marginsnotok) predictions disallowed 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

Functions e(sample) marks estimation sample


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