Hi All,
I have a proportion DV. I can't use the
Code:
fracreg
command because of my unit of analysis, so my regression is as follows:

Code:
xtgee y i.x1 x2 x3 x4 x5 x6 x7 x8 x9 x10 x11 x12, family(binomial 1) link(probit) corr(exchangeable) vce(robust)
I have a variable that I'm in interested in analyzing, x1, which is a binary variable coded as 0/1.

I found the link on fractional models (https://www.stata.com/stata14/fracti...utcome-models/) and dyex is used for margins. I tried to use dyex, but I couldn't, because it says factor variables not allowed with dyex. So, I decided to use
Code:
margins, dydx(*)  margins x1
I received the below results:
Code:
margins x1

Predictive margins                              Number of obs     =     13,405
Model VCE    : Semirobust

Expression   : Pr(y != 0), predict()

------------------------------------------------------------------------------
             |            Delta-method
             |     Margin   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
          x1 |
          0  |   .2681136   .0049269    54.42   0.000     .2584571    .2777702
          1  |   .3810374   .0503208     7.57   0.000     .2824105    .4796644
------------------------------------------------------------------------------
I had asked this question before, but now I'm wondering how to interpret the margin results above after finding this post (granted it's for a continuous variable)-- (https://www.statalist.org/forums/for...uous-variables).

Does this read that when x goes from 0 to 1 the proportion (y) increases by 11.3%? I found Richard Williams's Slides https://www3.nd.edu/~rwilliam/stats/Margins01.pdf. Are average marginal effects the same thing as average partial effects?

Lastly, I'm obviously not well-versed in econometrics, but is there another way to interpret the results of x1? With the margin command (EDIT: Or is it because of the regression?), if I interpreted correctly, it reads from 0 to 1 (for lack of better words). Is there a way to read the results as when x=1 (yes) or when x=0 (no) not as "when no goes to yes." (Again, sorry for the layman's terms. I gladly welcome better terminology).

Thank you.