[Rasch] counts to scale conversion

moritz heene moritz.heene at psychologie.uni-heidelberg.de
Tue Jan 24 19:49:57 EST 2006

Hello to all,

I agree with William Fisher, especially with "Regarding the model as an 
ideal disconnected from reality forgets that the data may be derived from 
questions that may be irrelevant, poorly formulated, or off-construct for 
some other reason, or that some respondents may not belong to the intended 
So I vote for 3. There is, of course, much to say about theories and formal 
models. But -in my opinion- Guttman hit the nail on the head by stating: 
"Scale analysis has been criticized by some on interesting grounds that it 
does not always 'succeed' like item analysis. Scales don't always exist, 
but people have come to believe that they MUST exist. And some researchers 
are frustrated if they can't construct scores with which to continue to be 
busy." (Psychometrika, 36(4), 1971).
--> The way I see it: the major advantage of the Rasch model is that it is 
essentially a falsifiable model.


Moritz Heene.

At 10:43 23.01.2006 -0500, you wrote:

>Content-class: urn:content-classes:message
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>Regarding the model as an ideal disconnected from reality forgets that the 
>data may be derived from questions that may be irrelevant, poorly 
>formulated, or off-construct for some other reason, or that some 
>respondents may not belong to the intended population.
>Why try to describe data that are not reproducible and replicable? How 
>well do we understand a construct when the only data we can produce are 
>not theoretically tractable, and so remain tied to particular questions 
>and respondents? It seems pretty cynical to me to do research with the 
>sole aim of applying fancy statistics to data, publishing articles, and 
>advancing ones own career, while deliberately limiting your potential for 
>generalizing your results past your own local samples of persons and items 
>because you choose models and methods that do not push you toward the 
>highest possible level of generality.
>I vote for 3. Strong construct theory is not automatically implied by 
>strong measurement theory. Being able to predict item difficulties when 
>the items have been previously calibrated is great, but the real goal is 
>to be able to predict their calibrations on the basis of their theoretical 
>properties, in the manner of Lexiles or Commonsstage scoring system.
>When we have this, then were getting somewhere. After all, imagine how 
>different our economic lives would be if rulers, weight scales, 
>thermometers, clocks, volt meters, and the resistance properties of every 
>meter of every type of electrical cable all had to be calibrated 
>individually on data, instead of en masse, by theory&.  Theoretical 
>predictability is the mark of a real science, where we understand a 
>variable to the point that we can recognize it for what it is in any 
>amount when we see it.
>After all, dont we say that a basic mark of knowing what were talking 
>about is being able to put it in our own words? Shouldnt any valid 
>articulation of a construct be a viable medium for measuring in a 
>univerally uniform reference standard metric?
>Jack Stenner has recently done some work describing several more than 
>three stages of this kind in the development of measurable 
>constructs&.  Maybe we can get him to weigh in&.
>William P. Fisher, Jr., Ph.D.
><mailto:WFisher at avatar-intl.com>WFisher at avatar-intl.com
>From: rasch-bounces at acer.edu.au [mailto:rasch-bounces at acer.edu.au] On 
>Behalf Of Agustin Tristan
>Sent: Monday, January 23, 2006 10:26 AM
>To: Tim Pelton; Rasch at acer.edu.au
>Subject: RE: [Rasch] counts to scale conversion
>Hi Tim...it could be nice to have further votes for the three options and 
>see how well this example fits to the person's opinion in this 
>listserve... or how well our opinions fit a model...
>Thank you.
>Tim Pelton <tpelton at uvic.ca> wrote:
>What a great example - and starting point for a discussion...
>My vote is for option 2.
>I think that the phrase in option 3 "...telling us (and the crickets too)..."
>demonstrates quite nicely the
>limitations of blindly applying an 'ideal' model. Is it reasonable to favor
>an elegant theoretical model
>that deviates substantially in it's predictions from the observed data when
>our lack of understanding of
>related factors means that we cannot effectively explain such deviations? Is
>it not more appropriate to
>choose a pragmatic model (balancing simplicity and accuracy) as an
>intermediate model to help us
>establish a control or baseline which may then be used to support our search
>for other factors?
>- >===== Original Message From Agustin Tristan =====
> >Hi! I'm trying to follow this topic concerning crickets and scales.
> > In abstract: Which is better?
> > 1) The simple linear model even if it doesn't fit (the linear model for the
>crickets' case).
> > 2) Any model who permits us to fit the data (the exp(something) looks to be
>like that).
> > 3) A theoretical model telling us (and the crickets too) how is the way
>crickets should adjust the
>frequency of the noise they produce according to temperature...specially if
>this theoretical model is
>exp(someting) because it looks more interesting or impressive.
> >
> > I like Nature and its relationship with math and for me it was interesting
>to know that crickets may
>use the exponential (even if they don't care about the mathematical
>formulation), as well as the seeds in
>sunflowers grow exponentially from their center, or the snails grow their
>shell, or the ivy plants grow in
>an helical 3D curve, or the soil slopes (in soil mechanics) become unstable
>and fail according to a
>logarithmic spiral, or the growth of populations follows a logistic model, and
>so forth... I can also
>recognize that I prefer objective items that behave as the Rasch model,
>but...I cannot decide in all those
>case which is better between (1), (2) and (3)...
> > Regards
> > Agustin Tristan
> >
> >Rense wrote:
> >
> >All this illustrates that if we want to stay in business as test gurus then
> >we'd better forget about meaningful item hierarchies, sample independence,
> >additive measures, and other such niceties. Rather, using methods whose
> >results need to be recalibrated for boys, girls, old, and young, ..,
> >whatever, ... - and adding a few things like "log(exp(something ...))" to
> >our tech reports - should greatly help with job security. :)
> >
> >Rense Lange
> >
> >-----Original Message-----
> >From: rasch-bounces at acer.edu.au [mailto:rasch-bounces at acer.edu.au]On
> >Behalf Of Trevor Bond
> >Sent: Saturday, January 21, 2006 5:43 PM
> >To: Rasch listserve
> >Subject: [Rasch] counts to scale conversion
> >
> >
> >For all budding scale constructors, this is a hoot:
> >http://www.dartmouth.edu/~genchem/0102/spring/6winn/cricket.html
> >check the lovely graphs
> >collegially
> >Trevor
> >--
> >Trevor G BOND Ph D
> >Professor and Head of Dept
> >Educational Psychology, Counselling & Learning Needs
> >D2-2F-01A EPCL Dept.
> >Hong Kong Institute of Education
> >10 Lo Ping Rd, Tai Po
> >New Territories HONG KONG
> >
> >Voice: (852) 2948 8473
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>Mariano Jiménez 1830 A
>Col. Balcones del Valle
>78280, San Luis Potosí, S.L.P. México
>TEL (52) 44-4820 37 88, 44-4820 04 31
>FAX (52) 44-4815 48 48
>web page (in Spanish AND ENGLISH): http://www.ieesa-kalt.com
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Dipl.-Psych Moritz Heene
AE Differentielle Psychologie und Psychologische Diagnostik
Psychologisches Institut
Universität Heidelberg
Hauptstr. 47-51
D-69117 Heidelberg

Tel.: +49 (0)6221-54 7281
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