**[TE] stteffects wra** -- Survival-time weighted regression adjustment

__Syntax__

**stteffects** **wra** **(***omvarlist* [**,** *omoptions*]**)** **(***tvar***)** **(***cmvarlist* [**,**
*cmoptions*]**)** [*if*] [*in*] [**,** *stat* *options*]

*omvarlist* specifies the variables that predict the survival-time variable
in the outcome model.

*tvar* must contain integer values representing the treatment levels.

*cmvarlist* specifies the variables that predict censoring in the censoring
model.

*omoptions* Description
-------------------------------------------------------------------------
Model
__weib__**ull** Weibull; the default
__exp__**onential** exponential
__gam__**ma** two-parameter gamma
__ln__**ormal** lognormal
**ancillary(***avarlist*[**,** __nocons__**tant**]**)** specify variables used to model
ancillary parameter
__nocons__**tant** suppress constant from outcome model
-------------------------------------------------------------------------

*cmoptions* Description
-------------------------------------------------------------------------
Model
__weib__**ull** Weibull; the default
__exp__**onential** exponential
__gam__**ma** two-parameter gamma
__ln__**ormal** lognormal
**ancillary(***avarlist*[**,** __nocons__**tant**]**)** specify variables used to model
ancillary parameter
__nocons__**tant** suppress constant from censoring
model
-------------------------------------------------------------------------

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

*options* Description
-------------------------------------------------------------------------
SE/Robust
**vce(***vcetype***)** *vcetype* may be __r__**obust**, __cl__**uster**
*clustvar*, __boot__**strap**, or __jack__**knife**

Reporting
__l__**evel(***#***)** set confidence level; default is
**level(95)**
__aeq__**uations** display auxiliary-equation results
__nosh__**ow** do not show st setting information
*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
**iterinit(***#***)** specify starting-value iterations;
seldom used

Advanced
__pstol__**erance(***#***)** set tolerance for overlap assumption
__os__**ample(***newvar***)** identify observations that violate
the overlap assumption
__con__**trol(***#*|*label***)** specify the level of *tvar* that is the
control
__tle__**vel(***#*|*label***)** specify the level of *tvar* that is the
treatment

__coefl__**egend** display legend instead of statistics
-------------------------------------------------------------------------

You must **stset** your data before using **stteffects**; see **[ST] stset**.
*omvarlist*, *cmvarlist*, and *avarlist* may contain factor variables; see
fvvarlists.
**bootstrap**, **by**, **jackknife**, and **statsby** are allowed; see prefix.
Weights are not allowed with the **bootstrap** prefix.
**fweight**s, **iweight**s, and **pweight**s may be specified using **stset**; see
*Weights* under *Remarks and examples* in **[ST] stset**. However, weights may
not be specified if you are using the **bootstrap** prefix.
**coeflegend** does not appear in the dialog box.
See **[TE] stteffects postestimation** for features available after
estimation.

__Menu__

**Statistics > Treatment effects > Survival outcomes >** **Weighted regression**
**adjustment**

__Description__

**stteffects wra** estimates the average treatment effect, the average
treatment effect on the treated, and the potential-outcome means from
observational survival-time data with random time to censoring.
Estimation is by weighted regression adjustment (WRA). WRA estimators
use inverse-probability-of-censoring adjusted regression coefficients to
compute averages of treatment-level predicted outcomes. Contrasts of
these averages estimate the treatment effects. WRA uses estimated
weights from a time-to-censoring model to account for censored survival
times instead of including a term in the likelihood function. **stteffects**
**wra** offers several choices for the functional forms of the outcome model
and the time-to-censoring model. Binary and multivalued treatments are
accommodated.

See **[TE] stteffects intro** for an overview of estimating treatment effects
from observational survival-time data.

__Options__

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

**ancillary(***avarlist*[**, noconstant**]**)** specifies the variables used to model
the ancillary parameter. By default, the ancillary parameter does
not depend on covariates. Specifying **ancillary(***avarlist***,** **noconstant)**
causes the constant to be suppressed in the model for the ancillary
parameter.

**ancillary()** may be specified for the model for survival-time outcome,
for the model for the censoring variable, or for both. If
**ancillary()** is specified for both, the varlist used for each model
may be different.

**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.

**noshow** prevents **stteffects wra** from showing the key st variables. This
option is rarely used because most people type **stset, show** or **stset,**
**noshow** to permanently set whether they want to see these variables
mentioned at the top of the output of every st command; see **[ST]**
**stset**.

*display_options*: **noci**, __nopv__**alues**, __noomit__**ted**, **vsquish**, __noempty__**cells**,
__base__**levels**, __allbase__**levels**, __nofvlab__**el**, **fvwrap(***#***)**, **fvwrapon(***style***)**,
**cformat(***%fmt***)**, **pformat(%***fmt***)**, **sformat(%***fmt***)**, and **nolstretch**; see **[R]**
**estimation options**.

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

*maximize_options*: __iter__**ate(***#***)**, [__no__]__lo__**g**, and **from(***init_specs***)**; see **[R]**
**maximize**. These options are seldom used.

*init_specs* is one of

*matname* [**,** **skip** **copy**]

*#* [**,** *#* ...]**,** **copy**

**iterinit(***#***)** specifies the maximum number of iterations used to calculate
the starting values. This option is seldom used.

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

**pstolerance(***#***)** specifies the tolerance used to check the overlap
assumption. The default value is **pstolerance(1e-5)**. **stteffects** will
exit with an error if an observation has an estimated propensity
score smaller than that specified by **pstolerance()**.

**osample(***newvar***)** specifies that indicator variable *newvar* be created to
identify observations that violate the overlap assumption.

**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 **stteffects** but is not shown in the
dialog box:

**coeflegend**; **[R] estimation options**.

__Examples__

Setup
**. webuse sheart**

Estimate the ATE, modeling the mean survival time using the default
Weibull outcome model
**. stteffects wra (age exercise diet education) (smoke)** **(age**
**c.age#c.age exercise diet education)**

Estimate the ATET, modeling the mean survival time using the default
Weibull outcome model
**. stteffects wra (age exercise diet education) (smoke)** **(age**
**c.age#c.age exercise diet education), atet**

__Stored results__

**stteffects** **wra** stores the following in **e()**:

Scalars
**e(N)** number of observations
**e(n***j***)** 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)** **stteffects**
**e(cmdline)** command as typed
**e(dead)** **_d**
**e(depvar)** **_t**
**e(tvar)** name of treatment variable
**e(subcmd)** **wra**
**e(omodel)** outcome model: **weibull**, **exponential**, **gamma**, or
**lognormal**
**e(cmodel)** censoring model: **weibull**, **exponential**, **gamma**, or
**lognormal**
**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