Example 17: Rack, stack, contrasts
Comparisons of measures at two time-points or in two situations can become complicated. Example 12 illustrates a straightforward situation. It uses the 13 motor items of the FIM®. This example uses the 18 items of the FIM, 13 motor and 5 cognitive, at two time points. There is a 7-level rating scale that is intended to operate in the same way across all items.
In exam17s.txt, the data have been stacked. The items are modeled to maintain their difficulties across the two time points, and the 52 patients are entered twice, once at admission to rehabilitation and once at discharge from it, so there 104 data records. Changes in patient independence can be identified by cross-plotting the admission and discharge measures for each patient, as in Example 12. This can be done by using the Plots menu to plot the measures against themselves, and then, in Excel, pasting the discharge measures over the top of the admission measures for the y-axis.
In exam17r.txt, the data have been racked. The persons are modeled to maintain their abilities across the two time points, and the 18 FIM items are entered twice, once at admission to rehabilitation and once at discharge from it, so there 36 items. Average changes in patient performance on individual items can be identified by cross-plotting the admission and discharge measures for each item. This can be done by using the Plots menu to plot the measures against themselves, and then, in Excel, pasting the discharge measures over the top of the admission measures for the y-axis.
A further feature is the contrasts in the Principal Components Analysis of Residuals, Tables 23 and 24. The 13 motor items and 5 cognitive items are probing different aspects of patient independence. Do they function as one variable in this sample? See Principal components/contrast. Patients also have different impairments. Are their measures comparable? See Differential Item Function.
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|Rasch Measurement Transactions (free, online)||Rasch Measurement research papers (free, online)||Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch||Applying the Rasch Model 3rd. Ed., Bond & Fox||Best Test Design, Wright & Stone|
|Rating Scale Analysis, Wright & Masters||Introduction to Rasch Measurement, E. Smith & R. Smith||Introduction to Many-Facet Rasch Measurement, Thomas Eckes||Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments, George Engelhard, Jr. & Stefanie Wind||Statistical Analyses for Language Testers, Rita Green|
|Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar||Journal of Applied Measurement||Rasch models for measurement, David Andrich||Constructing Measures, Mark Wilson||Rasch Analysis in the Human Sciences, Boone, Stave, Yale|
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|April 10-12, 2018, Tues.-Thurs.||Rasch Conference: IOMW, New York, NY, www.iomw.org|
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