Labels of facets and elements = (required)

This specification names each facet and follows it by a list of the element numbers and labels (names) to be included in the analysis.

 

Labels = (Nobuild)

Facet number ,

Facet label or name,

Anchoring,  (A,D,G,X)
+ No group reporting (N)

Estimation priority

Element number =

Element label or name,

Measure,

starting value, anchor value or group-anchor value

Group number,

for group-reporting or group-anchoring

Element weight,

defaults to 1.0

Target element number for merged elements: observations in the data with the Element number are assigned to the Target element number. Example:

1= , , , , 2 so that 1's become 2's in the data for this facet

*

 

1. Labels = (or if Labels= is omitted)

Facets adds to Output Table 2 a list of the elements in the data that are not specified in Labels=.

These can be copy-and-pasted into your specification file.

Specify Labels=Nobuild to omit the list of elements not specified in Labels= from Table 2.

 

2. Facet Identification

 

2A. Facet numbers

Choose the order you prefer to think about your facets, and number them in that order. The number you assign to each facet will determine the order in which the facets are reported.

If your facets are persons, judges and items, you may choose:

Facet 1: judges

Facet 2: persons

Facet 3: items

 

2B. Facet Anchoring

Choose the order you prefer to think about your facets, and number them in that order. The number you assign to each facet will determine the order in which the facets are reported.

If your facets are persons, judges and items, you may choose:

Facet 1: judges

Facet 2: persons

Facet 3: items

 

Facet

Anchor/Group code

Element Specification

Description

(None)

Element number = (label), (value), Group number

Group number is used for reporting groups of elements in Table 7

A

Element number = (label), Value, (group number)

Element measure is anchored at Value. Groups reported if there is a group number.

D

Element number = (label), (value), (group number)

Element measure is anchored at Umean= value. Groups reported if there is a group number.

G

Element number = (label), Value, Group number

Each element measure is measured independently but the sum of the measures of the group of elements are constrained to equal the sum of their Values.

X

Element number = (label), Value, Group number

The same as G, but elements with extreme scores (zero, perfect) are excluded.

...N

Element number = (label), (value), (group number)

This suppresses group reporting for a facet in Table 7.  Groups are ignored for measure reporting.

Labels=

2=Persons,GN ; group-anchoring wanted, but Table 7 does not report measures for each group separately

1=Ben,0,1 ; Ben is in group 1

2=Mike,0,2 ; Mike is in group 2

......

 

Valid Numerical Ranges

Facets

1 - 255

 

Any number in the range is valid. They do not need to start at 0 or 1, nor do they need to be in sequence.

Elements

Element numbers are in the range 1 - 2,147,438,648

 

Element 0 is usually the null element number, meaning "this facet does not apply to this observation." Element 0 can be used as an element number, provided Null element= is used to change the null element number from 0 to another number.

Group numbers

0 - 255

0 means "no group"

Observations

0 - 255 (can be rescored with Rating scale=)

 

2C. Estimation priority - Ignore this for most analyses.

This allows the measures for the elements of some facets to be estimated before the elements of other facets. For instance, facets modeling interaction terms can be estimated after their main effects have been estimated.

Priority 0: do not estimate the measures. This is equivalent to anchoring (A or D).

Priority 1: estimate the measures (the default)

Priority 2: estimate the measures after the Priority 1 measures have been estimated.

Priority 3: estimate after Priority 1 and 2.

Priority 4 and higher: estimate after higher priority measures have been estimated.

 

3. Element Identification

 

See Elements.


Help for Facets (64-bit) 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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