stats(scalarlist[, stats_subopts]) specifies one or more scalar
statistics - separated by white space - to be displayed at the bottom
of the table. The scalarlist may contain e() scalars and the
following statistics:
aic Akaike's information criterion
bic Schwarz's information criterion
rank rank of e(V), i.e. the number of free parameters in model
p the p-value of the model (overall model significance)
See help estimates for details on the aic and bic statistics. The
rules for the determination of p are as follows (note that although
the procedure outlined below is appropriate for most models, there
might be some models for which it is not):
1) p-value provided: If the e(p) scalar is provided by the
estimation command, it will be interpreted as indicating the
p-value of the model.
2) F test: If e(p) is not provided, estout checks for the
presence of the e(df_m), e(df_r), and e(F) scalars and, if
they are present, the p-value of the model will be calculated
as Ftail(df_m,df_r,F). This p-value corresponds to the
standard overall F test of linear regression.
3) chi2 test: Otherwise, if neither e(p) nor e(F) is provided,
estout checks for the presence of e(df_m) and e(chi2) and, if
they are present, calculates the p-value as
chi2tail(df_m,chi2). This p-value corresponds to the
Likelihood-Ratio or Wald chi2 test.
4) If neither e(p), e(F), nor e(chi2) is available, no p-value
will be reported.
The following stats_subopts are available. Use:
fmt(fmtlist) to set the display formats for the scalar statistics
in scalarlist. For instance, fmt(%9.3f %9.0f) would be a good
choice for stats(r2_a N). See help format. The last format in
fmtlist is used for the remaining scalars if scalarlist has
more elements than fmtlist does. Thus, only one format need
be specified if all scalars are to be displayed in the same
format. If no format is specified, the default format is the
display format of the coefficients.
labels(str_list[, label_subopts]) to specify labels for the
scalars in scalarlist. If specified, the labels are used
instead of the scalar names. For example:
. estout ..., stats(r2_a N, labels("Adj. R-Square"
"Number of Cases"))
star[(star_scalarlist)] to specify that the overall significance
of the model be denoted by stars. The stars are attached to
the scalar statistics specified in star_scalarlist. If
star_scalarlist is omitted, the stars are attached to the
first reported scalar statistic. The printing of the stars is
suppressed in empty results cells (i.e. if the scalar
statistic in question is missing for a certain model). The
determination of the model significance is based on the
p-value of the model (see above).
Hint: It is possible to attach the stars to different scalar
statistics within the same table. For example, specify
stats(,star(r2_a r2_p)) when tabulating OLS estimates and,
say, probit estimates. For the OLS models, the F test will be
carried out and the significance stars will be attached to
the r2_a; for the probit models, the chi2 test will be used