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I propose naming this approach the Jeffit estimator.

"We used Jeffit to estimate the average partial effects and their .95 CIs."

"We compare our main results with those obtained using Jeffit."

"We compare our main results with those obtained using Jeffit."

If you use @Stata to compute/estimate quantiles/percentiles there's a Statalist thread that may be of interest. (Spoiler: Different commands can yield different results—except for the median—so exercise care with tail-probability, IQR, etc. calculations.)

statalist.org/forums/forum/g…

statalist.org/forums/forum/g…

This is probably a negligible concern when analyzing most "large" samples, but not necessarily so for "small" ones.

Earlier threads have considered the use of the –recast– option in @Stata graphics. Here's another.

The –twoway function– command in Stata permits nice visualizations of explicit functions y=f(x) over some continuous domain of x-values. E.g.

twoway function y=normal(x), range(-3 3)

twoway function y=normal(x), range(-3 3)

This can be helpful in...

— visualizing comparative features of different explicit functions

— visualizing theoretical vs. empirical results (e.g. goodness-of-fit)

— etc.

— visualizing comparative features of different explicit functions

— visualizing theoretical vs. empirical results (e.g. goodness-of-fit)

— etc.