[Rasch] Facets feature or bug?

Bond, Trevor trevor.bond at jcu.edu.au
Mon Apr 2 17:30:29 EST 2012

Jason, I think this covers it:
Linacre (1997) displayed three judging rosters for ratings from the Advanced
Placement Program of the College Board. The complete judging plan of 1,152
ratings illustrates the ideal plan for both conventional and Rasch analysis.
This complete judging plan meets the connection requirement between all
facets because every element (essays, examinees, and judges) can be compared
directly and unambiguously with every other element.
A much less judge-intensive plan of only 180 ratings also is displayed, in
which less precise Rasch estimates can be obtained because the facet-linking
overlap is maintained. The Rasch measures would be less precise than with
complete data because 83% fewer observations are made. Linacre¹s final table
reveals the minimal judging plan, in which each of the 32 examinees¹ three
essays is rated by only one judge. Each of the 12 judges rates eight essays,
including two or three of each essay type, so that the examinee­judge essay
overlap of these 96 ratings still enables all parameters to be estimated
unambiguously in one frame of reference.
Of course, the saving in judges¹ costs needs to be balanced against the cost
of low measurement precision, but this plan requires only 96 ratings, 8% of
the observations required for the complete judging plan. Lunz et al. (1998)
reported the successful implementation of such a minimal judging plan
(Linacre, 1997).
B&F 2 p149

On 2/04/12 4:53 PM, "Iasonas Lamprianou" <liasonas at cytanet.com.cy> wrote:

> Dear all,
> I send this question to all, and not only to Mike, because this question is
> both related to the Facets software, but is a methodological question as well.
> I am running a "typical" scenario where I have markers who mark the responses
> of students to a test. The markers do not see the whole test, but only
> individual questions. We do NOT have double marking. So, lets say that we have
> 1000 students, each one responding to 10 questions. In effect, we have 10.000
> responses. Lets say that each one of the 10.000 responses is randomly sent
> once to one marker. We have 20 markers in total.
> Observation 1: the 3-d matrix markersXitemsXstudents is VERY sparse (we will
> all agree on that) because we have NO double marking
> Observation 2 which is a question as well: I think that the design is NOT
> linked (no double marking), does everyone agree? However, Facets does not
> complain about disconnected subsets, I do not know why. Should I not worry?
> Does Facets assume that because of randomness, all markers are on the same
> scale? Is Facets confused and incorrectly thinks that the design is NOT
> disconnected?
> Question: If disconnected subsets is a problem in this case, how can I run an
> anlysis in order to identify marker effects using this dataset?
> Thank you for your help
> Jason
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