{smcl}
{* 08AUG2009}{...}
{hline}
help for {hi:_grmargb}{right:08AUG2009}
{hline}
{title:Marginal effects and their differences from binary regressions using bootstrap method for inference}
{p 8 15 2}{cmd:_grmargb} [if] [in] [{cmd:,}
{cmd:x(}{it:variables_and_values}{cmd:)}
{cmd:rest(}{it:stat}{cmd:)}
{cmdab:l:evel(}{it:#}{cmd:)}
{cmdab:r:eps(}{it:#}{cmd:)}
{cmdab:si:ze(}{it:#}{cmd:)}
{cmd:save}
{cmd:diff}
{cmdab:noba:se}
{cmd:all match dots}]
{p 4 4 2}
where {it:variables_and_values} is an alternating list of variables
and either numeric values or mean, median, min, max, upper, lower,
previous and {it:stat} is either mean, median, min, max, upper, lower,
previous, grmean(group mean), mrmedian, grmin, grmax.
{title: Description}
{p 4 4 2}
{cmd:_grmargb} is a command that returns marginal effects, differences in
marginal effects and their confidence intervals using {help bootstrap} method
with resampling technique. It can calculate boostrapped confidence intervals
using the normal approximation, percentile, and bias-corrected methods.
{title: Options}
{p 4 8 2}
{cmd:x(}{it:variables_and_values}{cmd:)} sets the values of independent
variables for calculating predicted values (marginal effects). The list must alternate variable
names and either numeric values or types of {cmd:stat}.
{p 4 8 2}
{cmd:rest(}{it:stat}{cmd:)} sets the independent variables not specified
in {cmd:x(}{it:variables_and_values}{cmd:)} to one of the types of {cmd:stat}.
{p 4 8 2}
{cmd:level()} sets the {help level} of the confidence interval for differences in
group average marginal effects. The default is 95.
{p 4 8 2}
{cmd:reps(}{it:#}{cmd:)} specifies the number of bootstrap replications
to be performed. The default is 1000.
{p 4 8 2}
{cmd: size(}{it:#}{cmd:)} specifies the size of the samples to be drawn.
The default is e(N), the same size as the estimation sample.
{p 4 8 2}
{cmd:save} saves current values of independent variables and predictions
for computing changes using the diff option.
{p 4 8 2}
{cmd:diff} computes difference between current predictions and those that
were saved.
{p 4 8 2}
{cmd:nobase} suppresses inclusion of the base values of x in the output.
{p 4 8 2}
{cmd:all} specifies that any calculation of means, medians, etc., should
use the entire sample instead of the sample used to estimate the model.
{p 4 8 2}
{cmd:match} requests {cmd:grmargb} to resample from each category group
of the dependent variable in proportion of the resample size to the original
sample size.
{p 4 8 2}
{cmd:dots} requests a dot be placed on the screen at the beginning of each
replication, thus providing entertainment when a large number of reps() are
requested. It also prints out the percent replications finished.
{title: Returned Matrices}
{p 4 8 2}
r(marg): saves marginal effects.
{p 4 8 2}
r(margci): saves confidence intervals for marginal effects. Column 1 - 6 correspond to lower bounds, upper bounds for percentile
normal approximation, and bias-corrected methods.
{p 4 8 2}
r(margvar): saves variance-covariance matrix for marginal effects
{p 4 8 2}
r(margse): saves standard errors for marginal effects
{p 4 8 2}
r(dmarg): saves differences in marginal effects when {cmd:diff} option is used
{p 4 8 2}
r(dmargci): saves confidence intervals for differences in marginal effects when {cmd:diff} option is used. Column 1 - 6
correspond to lower bounds, upper bounds for percentile normal approximation, and bias-corrected methods.
{title:Examples}
{p 4 4 2}
To compute the predicted marginal effects, differences in marginal effects, and their confidence intervals using bootstrap method
for a logit model. All independent variables are held at their means except for black and education specifed in x().
{p 4 8 2}{cmd:.logit vote black educ income}
{p 4 8 2}{cmd:.grmargb, x(black=1 educ=16) save}
{p 4 8 2}{cmd:.grmargb, x(black=0 educ=16) diff}
{p 4 8 2}
:::
{hline}
{p 2 4 2}Authors: Jun Xu{p_end}