[Rasch] Facets feature or bug?

Parisa Daftari Fard pdaftaryfard at yahoo.com
Wed Apr 4 18:59:53 EST 2012


Dear Jason,
 
I had the same problem analyzing a set of data with the following features: 
1 there was a test consisting of several items each with several choices
2. a group of people rated the appropriacy of responses or choices only once
 
I used anchoring group in Facet. there Facet will anchor the scales. then you can copy and paste the result in your data file. 
 
Another way is to anchor at zero. then your data will be neutralized somehow for cross comparison.
 
in my data, I think if I had another facet like that rating one choice more than one time or some examinees producing choices, I would get a better result.
 
Best
Parisa
 
 
Parisa Daftarifard
PhD candidate of TEFL
IAU
Science and Research Branch
 


--- On Mon, 4/2/12, Iasonas Lamprianou <liasonas at cytanet.com.cy> wrote:


From: Iasonas Lamprianou <liasonas at cytanet.com.cy>
Subject: Re: [Rasch] Facets feature or bug?
To: rasch at acer.edu.au
Date: Monday, April 2, 2012, 12:41 PM



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. LinacreΉs final table
> reveals the minimal judging plan, in which each of the 32 examineesΉ 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 judgesΉ 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
> > Unsubscribe: 
> > https://mailinglist.acer.edu.au/mailman/options/rasch/trevor.bond%40jcu.edu.au
> > 
> 
> 
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