Stata 15 help for total

[R] total -- Estimate totals


total varlist [if] [in] [weight] [, options]

options Description ------------------------------------------------------------------------- if/in/over over(varlist[, nolabel]) group over subpopulations defined by varlist; optionally, suppress group labels

SE/Cluster vce(vcetype) vcetype may be analytic, cluster clustvar, bootstrap, or jackknife

Reporting level(#) set confidence level; default is level(95) noheader suppress table header nolegend suppress table legend display_options control column formats and line width

coeflegend display legend instead of statistics ------------------------------------------------------------------------- bootstrap, jackknife, mi estimate, rolling, statsby, and svy 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. vce() and weights are not allowed with the svy prefix. fweights, iweights, and pweights are allowed; see weight. coeflegend does not appear in the dialog box. See [R] total postestimation for features available after estimation.


Statistics > Summaries, tables, and tests > Summary and descriptive statistics > Totals


total produces estimates of totals, along with standard errors.


+------------+ ----+ if/in/over +-------------------------------------------------------

over(varlist [, nolabel]) specifies that estimates be computed for multiple subpopulations, which are identified by the different values of the variables in varlist.

When this option is supplied with one variable name, such as over( varname), the value labels of varname are used to identify the subpopulations. If varname does not have labeled values (or there are unlabeled values), the values themselves are used, provided that they are nonnegative integers. Noninteger values, negative values, and labels that are not valid Stata names are substituted with a default identifier.

When over() is supplied with multiple variable names, each subpopulation is assigned a unique default identifier.

nolabel specifies that value labels attached to the variables identifying the subpopulations be ignored.

+------------+ ----+ SE/Cluster +-------------------------------------------------------

vce(vcetype) specifies the type of standard error reported, which includes types that are derived from asymptotic theory (analytic), that allow for intragroup correlation (cluster clustvar), and that use bootstrap or jackknife methods (bootstrap, jackknife); see [R] vce_option.

vce(analytic), the default, uses the analytically derived variance estimator associated with the sample total.

+-----------+ ----+ Reporting +--------------------------------------------------------

level(#); see [R] estimation options.

noheader prevents the table header from being displayed. This option implies nolegend.

nolegend prevents the table legend identifying the subpopulations from being displayed.

display_options: cformat(%fmt) and nolstretch; see [R] estimation options.

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

coeflegend; see [R] estimation options.


Setup . webuse total

Estimate totals over values of sex, using swgt as pweights . total heartatk [pw=swgt], over(sex)

Stored results

total stores the following in e():

Scalars e(N) number of observations e(N_over) number of subpopulations e(N_clust) number of clusters e(k_eq) number of equations in e(b) e(df_r) sample degrees of freedom e(rank) rank of e(V)

Macros e(cmd) total e(cmdline) command as typed e(varlist) varlist e(wtype) weight type e(wexp) weight expression e(title) title in estimation output e(clustvar) name of cluster variable e(over) varlist from over() e(over_labels) labels from over() variables e(over_namelist) names from e(over_labels) 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(marginsnotok) predictions disallowed by margins

Matrices e(b) vector of total estimates e(V) (co)variance estimates e(_N) vector of numbers of nonmissing observations e(error) error code corresponding to e(b)

Functions e(sample) marks estimation sample

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