Michael Lamport Commons
commons at tiac.net
Thu May 8 10:02:28 EST 2008
I agree with Trevor. The best way to tease the variables apart is to identify them in the stimulus and then regress the single set of rasch scores on them. See if the r squares go up with two over one variable in a meaningful way. I am suggesting paying attention to dimensions of the stimuli, making the measurement problem into psychophysics rather than psychometrices. MLC
>From: Trevor Bond <trevor.bond at jcu.edu.au>
>Sent: May 7, 2008 7:12 PM
>To: luckyantonio2003 at yahoo.com, rasch at acer.edu.au
>Subject: Re: [Rasch] Unidimensionality
>what comes first, the measure or the residuals ?
>>In a couple of papers I noticed that the researchers before using
>>Rasch model or IRT models first use factor analysis to ascertain
>>unidimensionality. Since unidimensionality is a prerequisite to use
>>IRT models. They give the impression that only after FA has shown
>>that the test is unidimensioanl, one can use Rasch or IRT models.
>>Is this really necessary? Isn't the Rasch model itself a technique,
>>superior to FA, to demonstrate unidimensionality?
>my view is:
>1 find and remove the Rasch dimension
>2 use FA of the residuals to determine if sufficient structure exists
>in those residuals to infer more than one dimension in the data - the
>residuals should be randomly distributed.
>For mine: FA used before RM misses the point of RM
>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
>Fax: (852) 2948 7983
>Rasch mailing list
>Rasch at acer.edu.au
Michael Lamport Commons, Ph.D.
Assistant Clinical Professor
Department of Psychiatry
Harvard Medical School
Program in Psychiatry and the Law
Beth Israel Deaconess Medical Center
commons at tiac.net
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