Scalars
e(N) number of observations
e(mss) model 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(F) F statistic
e(rmse) root mean squared error
e(ll) log likelihood under additional assumption of i.i.d. normal errors
e(ll_0) log likelihood, constant-only model
e(N_clust) number of clusters
e(rank) rank of e(V)
Macros
e(cmd) regress
e(cmdline) command as typed
e(depvar) name of dependent variable
e(model) ols or iv
e(wtype) weight type
e(wexp) weight expression
e(title) title in estimation output when vce() is not ols
e(clustvar) name of cluster 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(marginsok) predictions allowed 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