Table 2 Data summary report

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Model=, Rating (or partial credit) scale= and Labels= control data selection for each analysisThis 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

35 =

*

4, Session, A ; facet 4

16 =

*

 

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 unmodelled data as well as modelled 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:

Labels=

1,Senior scientists

1=Avogadro

; element 2 is missing

3=Cavendish

*

Then, in Table 2 in the Report Output file:

Table 2. Data Summary Report.

.....

1, Senior scientists, ; facet 1

2 =

*

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

 

Table 2:

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 Publications
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 2nd. Ed., Bond & Fox (Winsteps) 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 (Facets) Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr. (Facets)
Statistical Analyses for Language Testers, Rita Green (Winsteps, Facets) Rasch Models: Foundations, Recent Developments, and Applications, Fischer & Molenaar Journal of Applied Measurement
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Coming Rasch-related Events
June 19-21, 2013, Wed.-Fri. SIS 2013 Conference on Advances in Latent Variables: Methods, Models and Applications, Brescia, Italy, meetings.sis-statistica.org/index.php/sis2013/ALV
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Sept. 18-20, 2013, Wed.-Fri. In-person workshop: Introductory Rasch (A. Tennant, RUMM), Leeds, UK, www.leeds.ac.uk/medicine/rehabmed/psychometric
Sept. 23-25, 2013, Mon.-Wed. In-person workshop: Intermediate Rasch (A. Tennant, RUMM), Leeds, UK, www.leeds.ac.uk/medicine/rehabmed/psychometric
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Dec. 11-13, 2013, Wed.-Fri. In-person workshop: Introductory Rasch (A. Tennant, RUMM), Leeds, UK, www.leeds.ac.uk/medicine/rehabmed/psychometric
March 12-14, 2014, Wed.-Fri. In-person workshop: Introductory Rasch (A. Tennant, RUMM), Leeds, UK, www.leeds.ac.uk/medicine/rehabmed/psychometric
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May 14-16, 2014, Wed.-Fri. In-person workshop: Introductory Rasch (A. Tennant, RUMM), Leeds, UK, www.leeds.ac.uk/medicine/rehabmed/psychometric
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