Stata 15 help for npregress_postestimation

[R] npregress postestimation -- Postestimation tools for npregress

Postestimation commands

The following postestimation commands are of special interest after npregress:

Command Description ------------------------------------------------------------------------- npgraph plot of conditional means -------------------------------------------------------------------------

The following standard postestimation commands are also available:

Command Description ------------------------------------------------------------------------- estat summarize summary statistics for the estimation sample estat vce variance-covariance matrix of the estimators (VCE) estimates cataloging estimation results lincom point estimates, standard errors, testing, and inference for linear combinations of coefficients margins marginal means, predictive margins, marginal effects, and average marginal effects marginsplot graph the results from margins (profile plots, interaction plots, etc.) nlcom point estimates, standard errors, testing, and inference for nonlinear combinations of coefficients predict predictions, residuals, influence statistics, and other diagnostic measures predictnl point estimates, standard errors, testing, and inference for generalized predictions test Wald tests of simple and composite linear hypotheses testnl Wald tests of nonlinear hypotheses -------------------------------------------------------------------------

Syntax for predict

predict [type] newvar [if] [in] [, statistic]

predict [type] {stub*|newvarlist} [if] [in], derivatives

statistic Description ------------------------------------------------------------------------- Main mean conditional mean of the outcome; the default residuals residuals ------------------------------------------------------------------------- These statistics are available for the estimation sample only.

Menu for predict

Statistics > Postestimation

Description for predict

predict creates a new variable containing predictions such as conditional mean of the outcome, residuals, or derivatives of the mean function.

Options for predict

+------+ ----+ Main +-------------------------------------------------------------

mean, the default, calculates the conditional mean of the outcome variable.

residuals calculates the residuals.

derivatives calculates the derivatives of the conditional mean.

Syntax for margins

margins [marginlist] [, options]

margins [marginlist] , predict(statistic ...) [options]

statistic Description ------------------------------------------------------------------------- Main mean conditional mean of the outcome; the default residuals not allowed with margins derivatives not allowed with margins -------------------------------------------------------------------------

options Description ------------------------------------------------------------------------- SE nose do not estimate standard errors; the default vce(vcetype) vcetype may be nose or bootstrap reps(#) equivalent to vce(bootstrap, reps(#)) seed(#) set random-number seed to #; must also specify reps(#)

Reporting citype(citype) method to compute bootstrap confidence intervals; default is citype(percentile) -------------------------------------------------------------------------

citype Description ------------------------------------------------------------------------- percentile percentile confidence intervals; the default bc bias-corrected confidence intervals normal normal-based confidence intervals -------------------------------------------------------------------------

Statistics not allowed with margins are functions of stochastic quantities other than e(b).

For the full syntax, see [R] margins.

Menu for margins

Statistics > Postestimation

Description for margins

margins estimates margins of the conditional mean.

Options for margins

+----+ ----+ SE +---------------------------------------------------------------

nose suppresses calculation of the VCE and standard errors. This is the default.

vce(vcetype) specifies the type of standard error reported, which may be either that no standard errors are reported (nose; the default) or that bootstrap standard errors are reported (bootstrap); see [R] vce_option.

We recommend that you select the number of replications using reps(#) instead of specifying vce(bootstrap), which defaults to 50 replications. Be aware that the number of replications needed to produce good estimates of the standard errors varies depending on the problem.

reps(#) specifies the number of bootstrap replications to be performed. Specifying this option is equivalent to specifying vce(bootstrap, reps(#)).

seed(#) sets the random-number seed. You must specify reps(#) with seed(#).

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

citype(citype) specifies the type of confidence interval to be computed. By default, bootstrap percentile confidence intervals are reported as recommended by Cattaneo and Jansson (2017). citype may be one of percentile, bc, or normal.

Syntax for npgraph

npgraph [if] [in] [, options]

options Description ------------------------------------------------------------------------- Plot marker_options change look of markers (color, size, etc.) marker_label_options add marker labels; change look or position noscatter suppress scatterplot

Smoothed line lineopts(cline_options) affect rendition of the smoothed line

Add plots addplot(plot) add other plots to the generated graph

Y axis, X axis, Titles, Legend, Overall twoway_options any options other than by() documented in [G-3] twoway_options -------------------------------------------------------------------------

Description for npgraph

npgraph plots the conditional mean estimated by npregress overlayed on a scatterplot of the data. npgraph is available only after fitting models with one covariate.

Options for npgraph

+------+ ----+ Plot +-------------------------------------------------------------

marker_options affect the rendition of markers drawn at the plotted points, including their shape, size, color, and outline; see [G-3] marker_options.

marker_label_options specify if and how the markers are to be labeled; see [G-3] marker_label_options

noscatter suppresses superimposing a scatterplot of the observed data over the smooth. This option is useful when the number of resulting points would be so large as to clutter the graph.

+---------------+ ----+ Smoothed line +----------------------------------------------------

lineopts(cline_options) affects the rendition of the smoothed line; see [G-3] cline_options.

+-----------+ ----+ Add plots +--------------------------------------------------------

addplot(plot) provides a way to add other plots to the generated graph; see [G-3] addplot_option.

+-----------------------------------------+ ----+ Y axis, X axis, Titles, Legend, Overall +--------------------------

twoway_options are any of the options documented in [G-3] twoway_options, excluding by(). These include options for titling the graph (see [G-3] title_options) and for saving the graph to disk (see [G-3] saving_option).

Examples

Setup . webuse dui

Nonparametric regression of citations as a function of fines . npregress kernel citations fines

Plot the estimated conditional mean function . npgraph

Add taxes as a discrete covariate . npregress kernel citations fines i.taxes

Estimate the mean number of citations when fines are increased by 15% . margins, at(fines=generate(fines*1.15))

Reference

Cattaneo, M. D., and M. Jansson. 2017. Kernel-based semiparametric estimators: Small bandwidth asymptotics and bootstrap consistency. Working paper. http://eml.berkeley.edu/~mjansson/Papers/CattaneoJansson_Bootstrappin > gSemiparametrics.pdf.


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