Table 6.0 All facet summary - Wright Map "rulers"

This is for 32-bit Facets 3.87. Here is Help for 64-bit Facets 4

Table 6 can be invoked from the Output Tables menu. Vertical= and Yardstick= control this Table. This set of rulers provides a graphical description of the variable as a Wright Map. The facets are positioned horizontally. The "+" or "-" before the facet name indicates whether the facet measures are positively or negatively oriented (Positive= or Negative=). The vertical axis provides a linear definition of the variable. Each element name is positioned according to its measure, "Measr". Elements with extreme scores are not positioned by measure, but are placed at the extreme top or bottom of the column for their facet.

 

The average expected response on the scale is indicated on the right-hand side. S.1 refers to scale 1 in Table 8.1. The "scale" column in Table 6 is the x-axis of the Expected Score ICC, also called the IRF. "---" are position at average expected half-score points. The extreme values of the scale are indicated by (_), e.g., (9) and (1).

 

It is easier to compare elements with the rating scale (or partial credit) when all facets are positively oriented: Positive= 1,2,3,....

 

To choose what to show in Facets Table 6, see Vertical=

To set the width of Table 6, see Yardstick=

 

The rating scale in the right-hand column is identified underneath the "Rulers": CREATIVITY

 


 

Using the rulers: "+ Junior scientist "5" ability - Attach difficulty - Cavendish severity" = average expected rating of "7".

 


 

Lines marked with ":" (instead of "|") are continuations of the lines above, and have the same measure.

In this example, Betty, Edward and George have different measures, but display on the same line. They are listed alphabetically.

 


 

Example 1. A published example

Table 6 as published in "Should candidate scores be adjusted for interviewer stringency or leniency in the multiple mini-interview?" by Chris Roberts, Imogene Rothnie, Nathan Zoanetti & Jim Crossley, Medical Education 2010: 44: 690–698
My red boxes: Notice that the logit range of the interviewers (raters) is about half that of the candidates. So that:

smartest candidate + most severe rater ≈ least smart candidate + most lenient rater

This was first noticed by Prof. Edgeworth around 1890, but 120 years later, Examination Boards continue to rely on the "luck of the draw" (as stated in Shavelson & Webb, "Generalizability Theory", 1991, p.8).

 


 

Example 2. Prettify the Creativity "rulers"

1. Do a standard Facets analysis of the Creativity data.
2. "Output Tables" menu
3. Table 6 (my setting: Yardstick = 1L, 2L, 3L)
4. Click on"Modify Specifications"
5. Click on "Ascii = Webpage"
6. click on OK
7. Temporary output file
8. Webpage displays
9. Reduce size until rulers are neatly visible (Ctrl -)
10. Copy and paste into a new Word document
11. Highlight all the Table with your mouse
12. Format font
13. 8pt
This should display neatly. If not,
14. 7pt (you can type in the 7 where the 8 was shown).

If there are spaces between the lines vertically, then

15. Format paragraph. Line spacing. Exactly. 6pt. (one point less than the font size)


Help for Facets Rasch Measurement and Rasch Analysis Software: www.winsteps.com Author: John Michael Linacre.
 

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Rasch Books and Publications
Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, 2nd Edn, 2024 George Engelhard, Jr. & Jue Wang Applying the Rasch Model (Winsteps, Facets) 4th Ed., Bond, Yan, Heene Advances in Rasch Analyses in the Human Sciences (Winsteps, Facets) 1st Ed., Boone, Staver Advances in Applications of Rasch Measurement in Science Education, X. Liu & W. J. Boone Rasch Analysis in the Human Sciences (Winsteps) Boone, Staver, Yale
Introduction to Many-Facet Rasch Measurement (Facets), Thomas Eckes Statistical Analyses for Language Testers (Facets), Rita Green Invariant Measurement with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments (Facets), George Engelhard, Jr. & Stefanie Wind Aplicação do Modelo de Rasch (Português), de Bond, Trevor G., Fox, Christine M Appliquer le modèle de Rasch: Défis et pistes de solution (Winsteps) E. Dionne, S. Béland
Exploring Rating Scale Functioning for Survey Research (R, Facets), Stefanie Wind Rasch Measurement: Applications, Khine Winsteps Tutorials - free
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Many-Facet Rasch Measurement (Facets) - free, J.M. Linacre Fairness, Justice and Language Assessment (Winsteps, Facets), McNamara, Knoch, Fan
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Rasch Measurement Transactions & Rasch Measurement research papers - free An Introduction to the Rasch Model with Examples in R (eRm, etc.), Debelak, Strobl, Zeigenfuse Rasch Measurement Theory Analysis in R, Wind, Hua Applying the Rasch Model in Social Sciences Using R, Lamprianou El modelo métrico de Rasch: Fundamentación, implementación e interpretación de la medida en ciencias sociales (Spanish Edition), Manuel González-Montesinos M.
Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch Rasch Models for Measurement, David Andrich Constructing Measures, Mark Wilson Best Test Design - free, Wright & Stone
Rating Scale Analysis - free, Wright & Masters
Virtual Standard Setting: Setting Cut Scores, Charalambos Kollias Diseño de Mejores Pruebas - free, Spanish Best Test Design A Course in Rasch Measurement Theory, Andrich, Marais Rasch Models in Health, Christensen, Kreiner, Mesba Multivariate and Mixture Distribution Rasch Models, von Davier, Carstensen
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