Facets requires specifications and data

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

Facets requires specifications and data. The data are qualitative observations. These are numbered in ascending sequence along the latent variable. For instance:

 

Qualitatively-ordered observations

must be exclusive, extensive, exhaustive

Numerical (scored, coded) observations:

higher number = more of the latent variable

must be 0 or positive integers

Yes-No

1-0

Correct-Incorrect

1-0

None-Some-All

0-1-2

Likert scale: Strongly Disagree-Disagree-Neutral- Agree-Strongly Agree

1-2-3-4-5

Essay rating

1-2-3-4-5-6-7-8-9

Attitude survey

1-2-3-4-5-6-7-8-9-10

Visual-analog scale or Percent

0-1-2-3-4-....-96-97-98-99-100

 

The specifications define how these data are modeled to be the outcome of a linear combination of elements. Each element belongs to a facet. All facets and elements are numbered. For instance:

 

Facet (number)

Elements (numbers)

Examinees (1)

Albert (1), Beryl (2), Claudia (3), ...

Raters (2)

Prof. Cilic (1), Dr. Nadal (2), Ing. Laver (3), ...

Items (3)

Item 1 (1), Item 2 (2), Item 3 (3), ...

Time-points (4)

Admission (1), Discharge (2)

 

The measurement model becomes:

Examinee ability + Rater leniency - Item difficulty - Time-point challenge Observation

 

a) Specifications are instructions on how to analyze the data. They are in the Facets specification file. They look like:

Specification = value

Most specifications have standard default values, suitable for most analyses.

 

Example 1: an excerpt from a list of specifications:

Title = Paired-judge Reading Test  ; the report heading line

Facets = 4   ; facets are 1=examinees, 2=raters, 3=items, 4=time-point

Positive = 1, 2  ; examinees are able, raters are lenient

Noncenter = 1   ; examinee measures float relative to raters, items, time-points

 

b) The data are the qualitative observations. Their location is specified by Data=. These can be in the same file as the specifications or in separate files. Each data point, response, observation or rating is analyzed as the interaction of one (or more) elements from each of the specified facets.

 

Example 2: an excerpt of Facets data:

Examinee 23 is rated by rater 4 on item 6 at time-point 2 with a rating of 7

Data=

23, 4, 6, 2, 7

 

Example 3: Here is a typical data file, after data collection:

123 A 25467 ; Examinee 123 is rated by judge A on items 1-5 with ratings 2, 5, 4, 6, 7

452 C 34245 ; Examinee 452, judge C, ratings 3, 4, 2, 4, 5

312 B 34452 ; Examinee 312, judge B, ratings 3, 4, 4, 5, 2

123 B 24443 ; Examinee 123, judge B, ratings 2, 4, 4, 4, 3

 

The Facets specification and data file:

 

Specification

Explanation

Title = Sample Analysis

The title of the analysis appears on every output report.

Facets = 3

There are 3 facets: examinees, judges, items.

Model = ?,?,?,R

The facets measurement model is: any examinee (?,) can combine with any rater (?,) and with any item (?,) to produce a rating (R)

Noncenter = 1

Center the elements all the facets except facet 1. This established the zero-point (local origin) of the measurement frame-of-reference.

Positive = 1, 2

Facets with "higher score = higher measure" (ability, leniency, easiness) are positive.

Facets with "higher score = lower measure" (disability, severity, difficulty) are negative.

Umean = 0, 1

The user-defined mean for the measures is zero. The user-defined scaling is 1. The reported measures will be in logits.

Labels =

The list of labels (identifiers) follows:

1,Examinees

123 = 

452 =

312 =

*

Facet 1 is the Examinees.

123 is the first examinee element.

453 is the second examinee

312 is another examinee

* is the end of Facet 1

2,Judges

1 = A

2 = B

3 = C

*

Facets 2 is the Judges

A is the label for the first judge, with element number 1.

3,Items

1-5

*

Facet 3 is the Items.

The item element numbers are 1, 2, 3, 4, 5

Data=

The data follows, or the data can be in a separate file: Data = filename.txt

123, 1, 1-5, 2, 5, 4, 6, 7

(comma-separated) Examinee 123 is rated by judge 1 (A) on items 1-5 with ratings 2, 5, 4, 6, 7

452 3 1-5 3 4 2 4 5

(blank separated) Examinee 452, judge 3 (C), items 1-5, ratings 3, 4, 2, 4, 5

31221-534452

(tab separated) Examinee 312, judge2 (B), items 1-5, ratings 3, 4, 4, 5, 2

123, B, 1-5, 2, 4, 4, 4, 3

Element labels are also allowed in the data. They will be automatically replaced by their element numbers

... more data


 

Look for a problem like yours in our examples. Then copy-and-edit it!

 

You can also use the template, Excel, SAS, SPSS, STATA and Facform.

 

End of Introductory Overview: Now start on your own! Run one of the Example files: how about the Diving Competition?


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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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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