Stata 15 help for areg

[R] areg -- Linear regression with a large dummy-variable set

Syntax

areg depvar [indepvars] [if] [in] [weight], absorb(varname) [options]

options Description ------------------------------------------------------------------------- Model * absorb(varname) categorical variable to be absorbed

SE/Robust vce(vcetype) vcetype may be ols, 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

coeflegend display legend instead of statistics ------------------------------------------------------------------------- * absorb(varname) is required. indepvars may contain factor variables; see fvvarlist. depvar and indepvars may contain time-series operators; see tsvarlist. bootstrap, by, fp, jackknife, mi estimate, rolling, and statsby are allowed; see prefix. vce(bootstrap) and vce(jackknife) are not allowed with the mi estimate prefix. Weights are not allowed with the bootstrap prefix. aweights are not allowed with the jackknife prefix. aweights, fweights, and pweights are allowed; see weight. coeflegend does not appear in the dialog box. See [R] areg postestimation for features available after estimation.

Menu

Statistics > Linear models and related > Other > Linear regression absorbing one cat. variable

Description

areg fits a linear regression absorbing one categorical factor. areg is designed for datasets with many groups, but not a number of groups that increases with the sample size. See the xtreg, fe command in [XT] xtreg for an estimator that handles the case in which the number of groups increases with the sample size.

Options

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

absorb(varname) specifies the categorical variable, which is to be included in the regression as if it were specified by dummy variables. absorb() is required.

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

vce(vcetype) specifies the type of standard error reported, which includes types that are derived from asymptotic theory (ols), 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.

vce(ols), the default, uses the standard variance estimator for ordinary least-squares regression.

Exercise caution when using the vce(cluster clustvar) option with areg. The effective number of degrees of freedom for the robust variance estimator is n_g - 1, where n_g is the number of clusters. Thus the number of levels of the absorb() variable should not exceed the number of clusters.

+-----------+ ----+ 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.

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

coeflegend; see [R] estimation options.

Examples

Setup . sysuse auto

Regression with fixed effects for rep78 . areg price weight length, absorb(rep78)

Same as above, but also compute the bootstrap standard errors . areg price weight length, absorb(rep78) vce(bootstrap, reps(200))

Stored results

areg stores the following in e():

Scalars e(N) number of observations e(k_absorb) number of absorbed categories e(mss) model sum of squares e(tss) total sum of squares e(df_m) model degrees of freedom e(rss) residual sum of squares e(df_r) residual degrees of freedom e(r2) R-squared e(r2_a) adjusted R-squared e(df_a) degrees of freedom for absorbed effect e(rmse) root mean squared error e(ll) log likelihood e(ll_0) log likelihood, constant-only model e(N_clust) number of clusters e(F) F statistic e(F_absorb) F statistic for absorbed effect (when vce(robust) is not specified) e(p) p-value for model F test e(p_absorb) p-value for F test of absorbed effect e(rank) rank of e(V)

Macros e(cmd) areg e(cmdline) command as typed e(depvar) name of dependent variable e(absvar) name of absorb variable e(wtype) weight type e(wexp) weight expression e(title) title in estimation output e(clustvar) name of cluster variable e(vce) vcetype specified in vce() e(vcetype) title used to label Std. Err. e(datasignature) the checksum e(datasignaturevars) variables used in calculation of checksum e(properties) b V e(predict) program used to implement predict e(footnote) program used to implement the footnote display 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 e(V_modelbased) model-based variance

Functions e(sample) marks estimation sample


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