CLFILE= codes label file
Rating (or partial credit) scale output is easier to understand when the categories are shown with their substantive meanings. Use CFILE= to label categories using their scored values, i.e., after rescoring. Use CLFILE= to label categories using their original codes, i.e., before any rescoring. Labels for the original categories in the data can be specified using CLFILE= and a file name, or CLFILE=* and placing the labels in the control file. Each category number is listed (one per line), followed by its descriptive label. Original category values are used. There are several options:
CLFILE= file name
file containing details
CLFILE = *
CLFILE = ?
opens a Browser window to find the file
Its format is:
item entry number + category code category label
%item label + category code category label
XWIDE=2 ;observations are two columns wide
CODES = " 0 1 299" ; codes are 0, 1 , 2, 99
99 Strongly Agree ; original code of 99 has the label "Strongly Agree"
2 Agree ; original code of blank+2 (or 2+blank) has the label "Agree"
2+99 Heartily Agree ; for item 2, code 99 has the label "Heartily Agree"
3+0 Disagree ; for item 3, code 0 means "Disagree"
Example 1: Identify the three LFS categories, D=Dislike, N=Don't know, L=Like.
The labels are shown in Table 3.2 as:
CATEGORY OBSERVED AVGE INFIT OUTFIT STRUCTURE
LABEL COUNT MEASURE MNSQ MNSQ MEASURE
0 378 -.87 1.08 1.19 NONE Dislike
1 620 .13 .85 .69 -.85 Don't know
2 852 2.23 1.00 1.46 .85 Like
Example 2: Items 1-10 (Grouping 1) are "Strong Disagree, Disagree, Agree, Strongly Agree". Items 11-20 (Grouping 2) are "Never, Sometimes, Often, Always".
7+A Strongly Disagree ; 7 is any item in Grouping 1
7+D Strong Agree
13+A Never ; 13 is any item in Grouping 2
Example 3: To enter CLFILE= information on the DOS Prompt or Extra Specifications lines, using commas instead of blanks as separators:
C:>Winsteps SF.TXT SFO.TXT CLFILE=* D,Dislike N,Don't-know L,Like *
Example 4: One grouping of items has a unique response format, but the other groupings all have the same format. Here, each grouping has only one item, i.e., ISGROUPS=0
1 Strongly Disagree ; This rating scale is used by most items
4 Strong Agree
16+1 Never ; 16 is the one item using this rating scale
Example 5: Several categories are collapsed into one category. The original codes are A-H. After rescoring there is only a dichotomy: 0, 1.
CODES = ABCDEFGH
0 Fail Specify the categories as recoded
Example 6: Identifying the distractors for a multiple-choice MCQ item.
Here is item 5:
5. The shape of the relationship between raw score and measures on the latent variable is
CODES = abcd
Example 7: Using the item labels
%APMED+9 NOT ASKED THAT YEAR
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|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 with Raters and Rating Scales: Rasch Models for Rater-Mediated Assessments, George Engelhard, Jr. & Stefanie Wind||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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