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2
Parallel Models
Parallel models are ordered regression models that impose the parallel regression
constraint for every independent variable in the model. In other words, the slopes do not
vary across cutpoint equations. As a result, parallel models are “ordinal” models in the
strictest sense of the term because the parallel regression assumption ensures a strict sto-
chastic ordering (McCullagh 1980, pp. 115–116), which we discussed in detail in Chapter1.
Parallel models are also the most parsimonious ordered regression models covered in this
book. Parallel models only require the estimation of one coefcient for each independent
variable ...