Bond, Yan, Heene (2020) Applying the Rasch Model 4th Edition Bond & Fox (2015) Applying the Rasch Model, 3rd Edition Bond & Fox (2007) Applying the Rasch Model, 2nd Edition Click here for a comparison of the functionalty of Bond&FoxSteps compared with Winsteps and Ministep Bond & Fox (2001) Applying the Rasch Model, 1st Edition ... Chapter 7: Pendulum InterviewYou will need to read the text of the book to understand these examples.
Official authors' website: Bond & Fox |
B&F Pendulum Interview data p. 97 The entire dataset is obtained from www.facebook.com/ApplyingTheRaschModelBondFox. The original data set contains 18 items and 58 children. Highlight with your mouse from here > Start Ministep. It should look exactly like the block above. "Save as" Click on Ministep or Winsteps on the bottom of your screen "Report output file name ..." "Extra specifications ..." Ministep runs. |
B&F Figure 7.1 paralled p. 99 You know what to do ... |
B&F Table 7.3 p. 101 Table 14 for the items in entry order for dichotomous item difficulties and item fit statistics. Winsteps Table 13: +--------------------------------------------------------------------------------------+ |ENTRY TOTAL MODEL| INFIT | OUTFIT |PTMEA| | |NUMBER SCORE COUNT MEASURE S.E. |MNSQ ZSTD|MNSQ ZSTD|CORR.| ITEM G | |------------------------------------+----------+----------+-----+---------------------| | 2 56 58 -2.48 .71|1.10 .4|1.16 .5| .05| 2 Order weights 0 | B&F Table 7.3 2 -2.36 .73 .3 .5 B&F Table 7.3 6.1 -2.41 1.25 .0 -.2 Corresponds to Winsteps 3.2 6 1 -2.58 1.04 1.02 .94 FOR GROUPING "0" ITEM NUMBER: 6 6 Infer +-------------------------------------------------------------------------- |CATEGORY STRUCTURE | SCORE-TO-MEASURE | 50% CUM.| COHERENCE|ESTIM| | LABEL MEASURE S.E. | AT CAT. ----ZONE----|PROBABLTY| M->C C->M|DISCR| |------------------------+---------------------+---------+----------+-----+ | 0 NONE |( -3.67) -INF -2.67| | 0% 0%| | 0 Not | 1 -2.53 1.04 | -1.10 -2.67 .46| -2.58 | 50% 27%| 1.02| 1 Action | 2 .32 .30 |( 1.46) .46 +INF | .38 | 72% 89%| 1.02| 2 Logic +-------------------------------------------------------------------------- Winsteps reports mean-squares (expected values = 1.0) for categories instead of t-statistics for thresholds. +------------------------------------------------------------------ |CATEGORY OBSERVED|OBSVD SAMPLE|INFIT OUTFIT||STRUCTURE|CATEGORY| |LABEL SCORE COUNT %|AVRGE EXPECT| MNSQ MNSQ||CALIBRATN| MEASURE| |-------------------+------------+------------++---------+--------+ | 0 0 1 2| -.15 -.03| .93 .78|| NONE |( -3.67)| 0 Not | 1 1 18 31| .74 .74| 1.02 .94|| -1.42 | -1.10 | 1 Action | 2 2 39 67| 1.47 1.47| .98 .99|| 1.42 |( 1.46)| 2 Logic +------------------------------------------------------------------ |
B&F Figure 7.2 p. 102 Table 12. Scroll down to 12.6. This pictures the 50% Cumulative Probability Thresholds |
Note: The Winsteps instructions on p. 104-105 are conceptual. |
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