[Rasch] Facets feature or bug?

Bond, Trevor trevor.bond at jcu.edu.au
Mon Apr 2 18:54:35 EST 2012


Sure, Jason
All your data seem to be linked via the students
As they are in the example given
Check Mike's paper
T


On 2/04/12 6:11 PM, "Iasonas Lamprianou" <liasonas at cytanet.com.cy> wrote:

> 
> thank you Trevor
> 
> i am afraid that i only have your edition one of the book, can i find this
> information there as well? also i apologise for not understanding fully your
> position so i need a clarification. your position is that it is not a bug and
> facets can recover some useful info to compare the raters although no double
> marking of any magnitude exists. am i missing something?
> 
> ----- Original Message Follows -----
> From: "Bond, Trevor" <trevor.bond at jcu.edu.au>
> To: "rasch at acer.edu.au" <rasch at acer.edu.au>
> Subject: Re: [Rasch] Facets feature or bug?
> Date: Mon, 2 Apr 2012 00:30:29 -0700
>> 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. Linacre?s final table
>> reveals the minimal judging plan, in which each of the 32 examinees? 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 judges? 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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>>> Rasch at acer.edu.au
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>>> au
>>> 
>> 
>> 
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