Data for analysis =

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

This tells Facets where to find the data.  Observations must be ordered integers in the range 0-254 for analysis. Facets can recode other data into integers using Rating Scale=

 

Either in the same file as the specifications:

Data =

followed by the data in the Facets data-format. This must be the last control specification, e.g.,

Data=

2,23,6,4 ;(The data)

0,13,9,1

3,4-6,8,1,5,4

 

Or in a separate data file or data files:

Data = diskfile.txt

where diskfile.txt is the name of the file containing the responses in the Facets data-format.

 

This can be extended to several data files with "+" signs:

Data = diskfile1.txt + diskfile2.txt + diskfile3.txt

 

or use %include file

Data =

%diskfile1.txt

%diskfile2.txt

%diskfile3.txt

 

The format of the diskfile.txt is determined by the filename suffix:

 

Suffix

Data= Format

.txt

text file (MS-DOS or Windows)

.xls .xlsx

Excel workbook: first or only worksheet

.rda .rdata

R data file

.sdata

SAS data file

.sav

SPSS data file

.dta

STATA 13 and earlier data file

(other)

text file (MS-DOS or Windows)

 

If the data file is not found, a file dialog box is displayed:

 

 

Please Edit Specification file, and Exit then restart the analysis.

 


 

Facets data format: Single observations

 

Facet 1

Facet 2

Facet ...

Observation

Element number

or Element label

or Dvalues=

Element number

or Element label

or Dvalues=

...

number

or value to recode with Rating-scale=

 

Facets data format: Multiple observations

 

Facet 1

Facet 2

Facet ...

Observation

Element number

or Element label

or Dvalues=

Element number range

(one facet, any facet)

...

numbers to match the element number range

or values to recode with Rating-scale=

 

Every line of data must have the same number of facet references (element numbers or element labels), usually given by Facets=. These facet references always appear in the same order. The element numbers are given in order by facet number, as specified after Labels=, unless overridden by Entered=. The facets references are then followed by one or more observed responses.

 

Example 1. Here is the flat file of observations:

123 665 25467

452 339 34245

312 034 34452

^   ^   ^

Examinee

   Judge

       Items 1 through 5

where format of flat file record is:

columns 1-3, "123" in record 1, are examinee identifiers

columns 5-7, "665" in record 1, are judge identifiers

columns 9-13, "25467" in record 1, are the ratings on items 1 to 5.

 

Convert this to Facets format. Insert commas and "1-5" added:

Labels=

1, Examinee

123

452

312

*

2, Judge

665

339

034

*

3,  Item

1-5

*

Dvalues = 3, 1-5  ; put 1-5 in third data facet

; Extra blanks in the data file are ignored,  also comments starting ";"

Data=

123 665 2 5 4 6 7 ; blanks are separators

452 339 3 4 2 4 5 ; "1-5" added from Dvalues=

312 034 "3" 4 4 5 2 ; values can be in quotes

 

Example 2: Data references recorded in facet number order with element labels

Labels=

2, Person ; Facet number 2 in the data

23=Fred

*

1, Judge ; The facet number, "1", not the order of definition, second, is what matters.

2=Hugo

*

3, Item

4=Sincerity

*

Data=

Hugo,Fred,4,1 ; Judge 2 (Hugo) rated Person 23 (Fred) on Item 4 (Sincerity) with a 1.

 

Example 3: Person 13 is rated on Item 4 by Judge 6 with a "3". This is data record is

Data=

13,4,6,3

 

Example 4: The data are letter grades, which are converted to numeric ratings by a Rating (or partial credit) scale= specification. Student 13's grade by Teacher 4 on Essay 1 is "B+"

Rating (or partial credit) scale=Grades,R9

9,Best,,A

7,B-Plus,,B+

*

Data=

13,4,1,B+

 

Example 5: Data references not in facet order. Entry= supplies both the order of the facet references and their identification in the data records:

Facets=4 ; 4 facets defined

Entry = 3,2,1 ; only 3 in data records, in different order

Model = ?,?,?,D ; first ? matches first reference, i.e., facet 3, etc.

Data =

4,23,2,1 ; Judge 2 (Hugo) rated Person 23 (Fred) on Item 4 (Sincerity) with a 1.

 

Example 6: Element number 0 of each facet is used to indicate that no element of that facet participated, e.g., Judge number 0 is used when no judge intermediated. Keepasnull= enables you to use 0 as an active element number. Thus, if a facet does not take part in an observation, element number 0 is recorded in the position in the data line for that facet, e.g.,

2,0,27,3 ; item 27 (facet 3) did not require a judge from facet 2 to rate it.

 

Example 7: Some data do not require references to some facets. Person 13 (facet 2) scored a 1 on item 9 (facet 3), which was not judged (facet 1). The judge element number is entered as 0 for that observation in the data:

0,13,9,1 ; element number in facet 1 is 0 (not participating)

 

Example 8: Multiple observations can be entered on the same data line, provided that the elements are in ascending or descending sequence by element number in one facet, and all other facets are the same. The extreme element numbers of the sequence are given, e.g., items 1 through 10 are indicated by 1-10,  Judge 2 (facet 1) gave person 23 (facet 2) on item 6 (facet 3) a response of 4, then

Judge 2 (facet 1) gave person 24 (facet 2) on item 6 (facet 3) a response of 5.

This can be recorded as

2,23,6,4

2,24,6,5

or, this can be recorded in one line as:

2,23-24,6,4,5 or 2,23_24,6,4,5

where the data points are entered to match the elements in the sequence.

The data points are also separated by commas ",".

 

Example 9: Person 3 (facet 1) took a 10 item test (items 1 through 10 of facet 2). He succeeded, scored 1, on items 1 to 5, and failed (scored 0) on items 6 to 10.

3,1-10,1,1,1,1,1,0,0,0,0,0 ; items ascending order

or

3,10-1,0,0,0,0,0,1,1,1,1,1 ; items descending order

or

3,1-4,0,0,0,0 ; some items ascending order

3,5-10,0,1,1,1,1,1 ; more items ascending order

 

Example 10: Missing observations: Person 13 is rated by Judge 8 on item 2 with a "3", item 3 with a "4", and item 6 with a "2". This is entered in the data file as

13,2-3,8,3,4 ; two observations in sequence

13,6,8,2 ; item not in sequence

or

13,2-6,8,3,4,,,2 ; items 4 and 5 entered as missing

 

Example 11: Dvalues= simplifies data formatting. The data are in a fixed format:

Person  Judge  Responses to items 1 to 6

13        4       134243

5       17       243223

These can be converted to Facets format by a word processor (Facets ignores blanks):

13  ,     4, 1-6, 1,3,4,2,4,3

5  ,    17, 1-6, 2,4,3,2,2,3

 

or

Dvalues = 3, 1-6  ; data facet 3 is 1-6

Data=

13  4 1 3 4 2 4 3 ; blanks are separators

 5 17 2 4 3 2 2 3 ; data facet 3 is 1-6

 

Example 12: Replication (weighting) of a data point can be specified by R (or another replication character) and the number of replications, for instance:

R3,2,23,6,4 means that the value of 4 was observed in this context 3 times.

Fractional replication permits flexible observation-weighting, see also Fractional models.

R3.5,2,23,6,4 means that the value of 4 was observed in this context 3.5 times.

 

Example 13: Organizing the ratings. There are three facets: examinees, tasks, raters. Each examinee performs two tasks that are rated by two raters:

Simplest:

examinee, task 1, rater A, rating

examinee, task 1, rater B, rating

examinee, task 2, rater A, rating

examinee, task 2, rater B, rating

 

or if the task element numbers are adjacent, then:

examinee, task 1-2, rater A, rating for task 1, rating for task 2

examinee, task 1-2, rater B, rating for task 1, rating for task 2

 

or if the rater element numbers are adjacent:

examinee, task A, rater 1-2, rating for rater 1, rating for rater 2

examinee, task B, rater 1-2, rating for rater 1, rating for rater 2

 

but NOT:

examinee, task 1-2, rater 1-2, rating, rating, rating, rating

 


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
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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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