#StackBounty: #r #regression #likelihood-ratio #ordered-logit Interpretation of ordinal regression output with RMS R package

Bounty: 50

Despite having read the documentation of the rms::orm() R package for fitting ordinal cumulative probability models, I am unclear on what models are being compared in the model likelihood ratio test that appears in the output. Is this comparing the proportional odds model to an analogous generalized logit non-proportional odds model?

An example of the relevant part of the output of a model of the form orm(y ~ x1 + x2, data = d) appears below for reference.

                        Model Likelihood               Discrimination    Rank Discrim.    
                              Ratio Test                      Indexes          Indexes    
 Obs          1463    LR chi2     354.50    R2                  0.216    rho     0.471    
 Distinct Y     19    d.f.             4    g                   1.049                     
 Median Y        8    Pr(> chi2) <0.0001    gr                  2.856                     
 max |deriv| 1e-08    Score chi2  357.09    |Pr(Y>=median)-0.5| 0.182                     
                      Pr(> chi2) <0.0001                                                  

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