﻿ 5 facet rating scale with bias analysis: Essays+Days

# 5 facet rating scale with bias analysis: Essays+Days

Using the Essays dataset, judge-day interactions are now to be examined. Since the day number is already coded in Facet 4, this can be implemented with Dvalues= without reformatting the data.

Facets specifications and data (in file Essayday.txt):

; this is file essayday.txt

title = AP English Essays (College Board/ETS)

facets = 5 ; there are 5 facets in this analysis

Model=

?,?B,?,?,?B, R9 ; look for interaction/bias between reader and day

*

Dvalues=

5, 4, 5, 1 ; day number: facet 5 of each observation from label for element in facet 4

; starting in column 5 of the label with a length of one.

*

noncenter = 1 ; examinee facet floats

positive = 1 ; for examinees, greater score = greater measure

inter-rater = 3 ; facet 3 is the rater facet

usort = 2,3,1 ; sort residuals by 2=Essay, 3=Reader, 1=Examinee

convergence = 0.1 ; size of largest remaining marginal score residual at convergence

unexpected = 3.0 ; size of smallest standardized residual to report

arrange = M ; arrange output tables in Measure ascending order

Labels=

1,examinee

1-32 ; 32 otherwise anonymous examinees

*

2,Essay

1,A ; 3 essays

2,B

3,C

*

1-12 ; 12 otherwise anonymous readers

*

4,Session,A ; this is a dummy facet

11,day 1 time 1 ,0 ; 8 sessions - all anchored at 0

12,day 1 time 2 ,0

21,day 2 time 1 ,0

22,day 2 time 2 ,0

31,day 3 time 1 ,0

32,day 3 time 2 ,0

41,day 4 time 1 ,0

42,day 4 time 2 ,0

*

5, Day, A ; this is a dummy facet, used only for investigating interactions

1, Day one, 0 ; Dvalues= obtains these from Facet 4.

2, Day two, 0

3, Day three, 0

4, Day four, 0

*

data =

05,1,1,11,4 ; first rating: examinee 5, essay 1, reader 1, session 11, rating of 4

| ; more data

09,1,1,11,3 ; last rating

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