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STS560 James Houran et al.
                •  The left-hand side represents the ratio of Pijk over Pik(k-1), i.e., the log
                    odds  of  observing  a  rating  in  category  k  relative  to  probability  of
                    observing one in category k-1.
                •  Tj represents the trait level (or ability) of person j, and most applications
                    focus on the Tj only.
                •  Di is the “difficulty” of  the item, or the magnitude of the trait level
                    needed to elicit the response k. Higher values of D indicate that higher
                    trait levels are needed to obtain a higher rating.
                •  In general, higher D yields lower ratings and higher T will yield higher
                    ratings.
                •  As the trait level Tj increases we expect to see the categories 0, 1, 2, ….,
                    m to be used in this order – at least probabilistically. The Fik denote the

                    locations at which the ratings k and k-1 are equally likely, and such Fik
                    are typically referred to as “step-values.”
                •  Although the following assumes that items share the same step-values,
                    the subscript i indicates that the step-values are actually allowed to
                    vary  across  items.  We  use  the  convention  that  ∑k  Fik  =  0  and  it  is
                    mathematically convenient to define Fi0 = 0.
                •  Note that all parameters vary along the same latent trait variable and
                    they are expressed in the same unit of measurement, i.e., the logit as
                    defined by the left-hand side of Equation 1.

            3.  Example
                The various definitions are illustrated in Figure 2 which shows the Pijk of
            each rating k for a rating scale with four categories (“Disagree Completely,”
            “Disagree Somewhat,” “Agree Somewhat,” and “Agree Completely”) across the
            underlying latent Rasch dimension. In the example, Di = 0 and Fk = {0, -1.37,
            0.14, 1.23}, and these step-values are shown relative to Di. It can be seen that
            for very low trait levels the rating “Disagree Completely” is virtually certain, but
            that “Disagree Somewhat” becomes equally likely at -1.37 logits and the latter
            is more likely above this point. Similarly, “Disagree Somewhat” and “Agree
            Somewhat” are equally likely at 0.14 logits, and “Agree Somewhat” and “Agree
            Completely” are equally likely at 1.23 logits. Note that the Pijk sum to unity
            across the various categories. For instance, at -0.9 logits (solid vertical line) the
            probabilities of the 4 categories (in order) are about 0.31, 0.45, 0.21, and 0.03,
            respectively.

            4.  Background
            Obtaining images such as Figure 2 requires solving for Pijk in Eq. 1:

                        
                    exp ∑ =0 [  −  −  ]
               =  ∑   exp ∑  =0 [  −  −  ]             = 0, 1, … ,                                                            (2)
                   =0

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