Table 31.5, 31.6 Within-class fit report
Table 31.5 Within-class fit report (item class within person).
Table 31.6 Within-class fit report (person class within item)
DIF class specification is: DIF=@GENDER
| TAP OBSERVATIONS BASELINE W-INFIT W-OUTFIT KID |
| CLASS COUNT AVERAGE EXPECT MEASURE MNSQ ZSTD MNSQ ZSTD Number Name |
| 1 11 .18 .23 -2.94 .71 -.5 .25 -.3 1 Adam M|
For a general description, see Table 31.2
The DPF effects are shown ordered by CLASS within person (row of the data matrix).
TAP CLASS identifies the CLASS of items. KID is specified with ITEM=, e.g., the first CLASS is "1-"
OBSERVATIONS are what are seen in the data
COUNT is the number of observations of the classification used for DPF estimation, e.g., 11 "1-" items responses were made by person 1.
AVERAGE is the average observation on the classification, e.g., 0.18 is the average score class "1-' items by person 1.
COUNT * AVERAGE = total score of person on the item class.
BASELINE is the prediction without DPF
EXPECT is the expected value of the average observation when there is no DPF, e.g., 0.92 is the expected average for person 1 on item class "1-" without DPF.
MEASURE is the what the overall ABILITY measure would be without DPF, e.g., -2.94 is the overall person ability of person 1 as reported in Table 18.
W-INFIT is the Within-Group infit statistic for the item CLASS on the person.
W-OUTFIT is the Within-Group outfit statistic for the item CLASS on the person.
MNSQ is the mean-square statistic (chi-square divided by its degrees of freedom).
ZSTD is the mean-square statistic expressed as a z-score (unit normal deviate).
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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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|April 10-12, 2018, Tues.-Thurs.||Rasch Conference: IOMW, New York, NY, www.iomw.org|
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|June 27 - 29, 2018, Wed.-Fri.||Measurement at the Crossroads: History, philosophy and sociology of measurement, Paris, France., https://measurement2018.sciencesconf.org|
|June 29 - July 27, 2018, Fri.-Fri.||On-line workshop: Practical Rasch Measurement - Further Topics (E. Smith, Winsteps), www.statistics.com|
|July 25 - July 27, 2018, Wed.-Fri.||Pacific-Rim Objective Measurement Symposium (PROMS), (Preconference workshops July 23-24, 2018) Fudan University, Shanghai, China "Applying Rasch Measurement in Language Assessment and across the Human Sciences" www.promsociety.org|
|Aug. 10 - Sept. 7, 2018, Fri.-Fri.||On-line workshop: Many-Facet Rasch Measurement (E. Smith, Facets), www.statistics.com|
|Sept. 3 - 6, 2018, Mon.-Thurs.||IMEKO World Congress, Belfast, Northern Ireland www.imeko2018.org|
|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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