Example 8: Items with various rating scale or partial credit models |
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A A |
A 4 item test in which each item has a 9-level scoring rubric. We suspect that there are not really 9 levels of competence. After several WINSTEPS analyses, we choose to recode the rating scale or partial credit items by collapsing categories in order to increase measurement effectiveness (separation) and increase parameter stability. An objection to collapsing is that it violates the Rasch model. This is only true if the uncollapsed data strictly accord with the model. In fact, the collapsed data may fit the Rasch model better than the uncollapsed. We have to compare the collapsed and uncollapsed analyses to decide.
; This file is EXAM8.TXT
TITLE="Success and Failure Items"
NAME1=6
ITEM1=1
NI=4 ; 4 items
ISGROUPS=1234 ; one item per grouping, same as ISGROUPS=0
IREFER=ABCD ; the 4 items are to be recoded differently. Item 1 is type "A", etc.
CODES=123456789 ; the codes in the data file
IVALUEA=333456666 ; the recoding for A-type items in IREFER=, i.e., Item 1
IVALUEB=333455555
IVALUEC=333444444
IVALUED=444456777
&END
Maze
Passengers
Blocks
Egg race
END NAMES
5536 M Richard
4545 F Tracie
4345 M Walter
3454 M Blaise
4435 M Ron
....
Table 14.3 shows the recoding:
ITEMS CATEGORY/OPTION/Distractor FREQUENCIES: ENTRY ORDER
+------------------------------------------------------------------------+
|ENTRY DATA SCORE | DATA | USED AVERAGE OUTF| |
|NUMBER CODE VALUE | COUNT % | COUNT % MEASURE MNSQ| ITEM |
|--------------------+------------+--------------------------+-----------|
| 1 2 3 | 1 3 | 1 3 -2.39 .3|Maze |
| 3 3 | 7 22 | 6 19 -1.57 .7| |
| 4 4 | 10 31 | 10 32 -.54 .5| |
| 5 5 | 10 31 | 10 32 1.23 .6| |
| 6 6 | 3 9 | 3 10 2.42 .7| |
| 7 6 | 1 3 | 1 3 2.78 .5| |