Table 2 Data summary report
Model=, Rating (or partial credit) scale= and Labels= control data selection for each analysis. This confirms that your data has been understood in the way you expected. If the counts in this table are unexpected, examine your data, Labels= and Model= specifications. If an element number is missing from the Labels= specifications, then all its data values may have been ignored.
Table 2. Data Summary Report.
Assigning models to "C:\Facets\Examples\Essays.txt"
Check (1)? Unspecified element: facet: 4 element: 16 in line 1198 - see Table 2
Check (2)? Invalid datum location: 1,1,b in line 52. Datum "b" is too big or not a positive integer, treated as missing.
Total lines in data file = 1154
Total data lines = 1154
Responses matched to model: ?,?B,?B,?,R9,1 = 1152
Total non-blank responses found = 1153
Number of blank lines = 1
Responses with unspecified elements = 1
Number of missing-code observations = 1 (,x,y,)
Valid responses used for estimation = 1152
List of unspecified elements. Please copy and paste into your specification file, where needed
Labels=Nobuild ; to suppress this list
1, examinee, ; facet 1
4, Session, A ; facet 4
Total lines in data file =
is the number of lines in your data file, or following the Data= specification in your specification file. It includes blank lines, comments (;), and unmodeled data as well as modeled data.
Total non-blank responses found =
This is a count of all non-blank responses in your data file.
Responses with unspecified elements =
Elements referencing elements not specified after Labels= are dropped from the analysis, unless for facets marked "X" in Model= statements. To obtain information about the unspecified elements, specify Query=Y.
Example: Check (1)? Unspecified element: facet: 1 element: 13 in line 2594
In the data, line 2594, facet 1 has element number 13.
In the Labels= list, under facet 1, there is no element 13. So the data is treated as unspecified.
If you want to analyze it, add 13 to the element list for facet 1. Also any other similar elements.
Facets only reports the first unspecified element found, so Facets may report another element as unspecified after you account for element 13.
Valid responses used for estimation =
This is a count of those responses in your data file which matched your model statements and were used in the analysis. It is 0 if no useable data was found.
Responses matched to model: (model description) =
This is a count of how many responses matched the particular model. This is useful for validation of model specifications. Invalid data values and models specifying data to be treated as missing are included here, but not in the "Valid responses found" count.
Example 1: I removed one element number in Guilford.txt:
; element 2 is missing
Then, in Table 2 in the Report Output file:
Table 2. Data Summary Report.
1, Senior scientists, ; facet 1
So, I can copy-and-paste 2 = into Guilford.txt. Then that element number will not be missing.
Example 2: A facet does not apply to these data:
Facets = 3
Keepasnull = 0 ; this element number is ignored
Data = 1,2,0, 4 ; facet 3 element 0 is because facet 3 does not apply to these data
Labels=Nobuild ; to suppress this list
3, Facet 3
0 = ; this element number is ignored, because Keepasnull=0 - this is only a warning
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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|
|in Spanish:||Análisis de Rasch para todos, Agustín Tristán||Mediciones, Posicionamientos y Diagnósticos Competitivos, Juan Ramón Oreja Rodríguez|
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|Oct. 12 - Nov. 9, 2018, Fri.-Fri.||On-line workshop: Practical Rasch Measurement - Core Topics (E. Smith, Winsteps), www.statistics.com|
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