Survey Analysis and Rasch

The Michigan Department of Education and Employability Skills Task Force distribute a survey designed to identify the critical skills, behaviors and attitudes employers want in employees. Respondents rate 86 items as critical, highly needed, somewhat needed or not needed. In 1989, Michigan public school principals asked elementary and secondary teachers to fill out this survey.

Conventional survey analysis depends on insupportable assumptions about the numerical values of response categories. An interval scale must be specified on which critical might be valued at, say, 4, highly needed at 3, somewhat needed at 2, and not needed at 1. But there is no objective basis for assigning or means of confirming any particular choice of values. Rasch analysis requires only that response categories are coded in a qualitatively increasing order. The working "values" of the responses are estimated from the data. This reflects the views of the survey respondents more accurately than the conventional method.

The Rasch step calibrations for the teachers were:

       STEP TO               SECONDARY  ELEMENTARY
  not needed                    N/A        N/A
  somewhat needed               -.92      -1.03
  highly needed                 -.72       -.47
  critical                      1.64       1.50

This shows that these teachers regarded the steps from not needed to somewhat needed and from somewhat needed to highly needed as closer in value than the final step to critical. The region along the continuum in which the response somewhat needed stood out was so brief that little information was conveyed by the use of that category. In general, skills were either not needed, highly needed, or critical.

Conventionally, misfitting items are those with high raw response standard deviations. Rasch misfitting items are those for which no clear "latent scale" has been manifested. These contrasting types of misfit affected much the same items for secondary school teachers, but totally different items for elementary teachers demonstrating that Rasch misfit is not necessarily identical to conventional misfit. The Rasch analysis provided the more useful interpretation.



Survey Analysis and Rasch, William L. Brown … Rasch Measurement Transactions, 1990, 4:2 p.106


Please help with Standard Dataset 4: Andrich Rating Scale Model



Rasch Publications
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: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. 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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