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Partial Models
Partial models are ordered regression models that relax the parallel regression assumption
for one subset of variables. Relaxing the parallel assumption allows the coefcients in this
group to vary across the cutpoint equations. In other words, some variables will have coef-
cients that change depending on the level of the dependent variable. The parallel regres-
sion assumption ensures that the model is “ordinal” in the strictest sense (see McCullagh
1980, pp. 115–116). Therefore, partial models are only strictly ordinal with respect to the set
of independent variables with the parallel assumption. Ordinal patterns may emerge ...