I am fitting a model predicting a person's perceived odds of having cardio-risk (measured via 3 -categories)
-- No Risk
-- Low Risk
-- High Risk

Brant test indicated need for ordered logit approach, so I am using gologit2 for the analysis. I've consulted the documentation on gologit2 and read Dr. William's materials as well, and attempted an interpretation of the output, but I want to be sure I am making the right contrasts/comparisons appropriately:

Here is my command and output, and my interpretation follows:

Code:
set more off
gologit2 cardiorisk age i.sex i.fam_hist yrsusa ///
i.lowcarb i.friends_sameethnic educ i.friends_risk ///
 , auto lrforce


------------------------------------------------------------------------------
Testing parallel lines assumption using the .05 level of significance...

Step  1:  Constraints for parallel lines imposed for age (P Value = 0.6247)
Step  2:  Constraints for parallel lines imposed for i.fam_hist (P Value = 0.4300)
Step  3:  Constraints for parallel lines imposed for i.sex (P Value = 0.3468)
Step  4:  Constraints for parallel lines imposed for yrsusa (P Value = 0.2823)
Step  5:  Constraints for parallel lines are not imposed for
          educ (P Value = 0.00081)
          i.lowcarb (P Value = 0.00543)
          i.friends_sameethnic (P Value = 0.00227)
          i.friends_risk (P Value = 0.01911)

------------------------------------------------------------------------------

Generalized Ordered Logit Estimates             Number of obs     =        496
                                               
---------------------------------------------------------------------------------------
         cardiorisk   |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
none  
                      |
                educ  |   .0267677   .0509569     0.53   0.599     -.073106    .1266415
                      |
            lowcarb   |   .9560091   .2417372     3.95   0.000     .4822129    1.429805
                      |
   friends_sameethnic |   .1248707    .392147     0.32   0.750    -.6437233    .8934647
   
                age   |   .0193308   .0113127     1.71   0.087    -.0028417    .0415033
           sex_female |  -.2504234    .195122    -1.28   0.199    -.6328555    .1320088
            fam_hist  |   .6090692   .1892519     3.22   0.001     .2381422    .9799962
            yrsusa    |  -.8336397   .3744464    -2.23   0.026    -1.567541   -.0997383
     
                _cons |  -1.148632   .9356265    -1.23   0.220    -2.982427    .6851618
----------------------+----------------------------------------------------------------
low                   |
 
        friends_risk  |   2.038412   .3153763     6.46   0.000     1.420285    2.656538
        
                age   |   .0193308   .0113127     1.71   0.087    -.0028417    .0415033
           sex_female |  -.2504234    .195122    -1.28   0.199    -.6328555    .1320088
            fam_hist  |   .6090692   .1892519     3.22   0.001     .2381422    .9799962
            yrsusa    |  -.8336397   .3744464    -2.23   0.026    -1.567541   -.0997383
                      |
                _cons |  -.3649326   .9573218    -0.38   0.703    -2.241249    1.511384
                
=======================================================================================
MY ATTEMPTED INTERPRETATION

Constrained Factors - Interpretation

- Higher cardiovascular risk perception is higher for those with a family history of cardiovascular illness
- By contrast, lower risk perception associated with increasing US residence


Unconstrained Factors (No Risk vrs Low/High Risk) - Interpretation

- Eating low carb diet is associated with having NO risk perception, compared to having at least (low + high) risk perception


Unconstrained Factors (No+Low vrs High Risk) - Interpretation

- a persons self-perceived cardio risk is associated that of their friends: having friends who are similarly
perceived as having lower risk perception (none + low) compared to high, tends to positively influence one's risk perception.


I would very much appreciate some thoughts on whether i am interpreting this output correctly, particularly with regard to the comparisons between the various categories of the DV.

Sincerely, cY