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# st: st: Interpreting mfx & margeff Coefficients from GLM

 From "Clifton Chow" To statalist@hsphsun2.harvard.edu Subject st: st: Interpreting mfx & margeff Coefficients from GLM Date Mon, 02 Apr 2012 16:01:40 -0500

```Stata listers,

I ran a glm log link (family gamma from modified park's test) on my dataset in which the dependent variables is hours worked.  To interpret the coefficients in the model, I transformed it via mfx and margeff.  I have a couple of questions about interpreting the coefficients after transformation;

1. Is mfx mainly appropriate for indicator explanatory variables and margeff for continous ones?
2. Can I interpret the results of the mfx coefficients in the raw scale (i.e. hours)?
3. What does the column in the far right X referred to in the mfx output?

Below is my partial mfx output from GLM:

y  = Predicted mean hours (predict)
=  8.7005381
------------------------------------------------------------------------------------------------
variable |      dy/dx    Std. Err.     z    P>|z|  [    95% C.I.   ]      X
---------+--------------------------------------------------------------------------------------
X1*|   8.891796     1.83527    4.84   0.000   5.29474  12.4889   .237385
X2*|  -5.151794     1.41499   -3.64   0.000  -7.92513 -2.37846   .519545
(*) dy/dx is for discrete change of dummy variable from 0 to 1

4. For margeff, to interpret these in hours, should I exp(margeff coefficient)?

Average partial effects after glm
y  = log(hours)

------------------------------------------------------------------------------
variable |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
X1         |      16.5519     3.9611     4.18   0.000     8.788287    24.31551
X2         |  -7.379914   1.553438    -4.75   0.000     -10.4246   -4.335232

Thanks
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```