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IDANET  January 2007

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Subject:

Re: Parscale

From:

Stephen Z Levine <[log in to unmask]>

Reply-To:

IDANET (Individual Differences and Assessment Network)

Date:

Wed, 17 Jan 2007 17:31:33 +0200

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (188 lines)

Hi
Why not use the ltm 
package of R?
www.r-project.org 
S.

----- Original Message ----- 
From: "Iasonas Lamprianou" <[log in to unmask]>
To: <[log in to unmask]>
Sent: Wednesday, January 17, 2007 8:22 AM
Subject: Re: Parscale


> Thanks,
> do you happen to know his email address?
> Jason
> 
> ----- Original Message Follows -----
> From: "A. Beaujean" <[log in to unmask]>
> To: [log in to unmask]
> Subject: Re: Parscale
> Date: Tue, 16 Jan 2007 14:11:52 -0600
>> You can contact Leo Stamm (Sp?) at SSI about the issue. He
>> does a good job at getting back with you, but as far as I
>> can tell, it is just part of the problem with the SSI IRT
>> suite. That is, it requires a lot of monkeying around to
>> get convergence on some data sets.
>> 
>> On 1/16/07, Iasonas Lamprianou <[log in to unmask]>
>> wrote: >
>> > Thanks for sharing your experience Alex,
>> > but does anyone have a solution? Or I think this is a
>> > problem of all IRT software? Anyway, how much can you
>> > trust a software with such a peculiar behaviour?
>> >
>> > Jason
>> >
>> > ----- Original Message Follows -----
>> > From: "A. Beaujean" <[log in to unmask]>
>> > To: [log in to unmask]
>> > Subject: Re: Parscale
>> > Date: Tue, 16 Jan 2007 13:30:38 -0600
>> > > I have a similar thing happen in BILOG-MG when I have
>> > > a large data set. When I put priors in the parameters,
>> > > it sometimes works; likewise, changing the number of
>> > > quadrature points.
>> > >
>> > > Alex
>> > >
>> > >
>> > > On 1/16/07, Iasonas Lamprianou
>> > > <[log in to unmask]> wrote: >
>> > > > Dear friends,
>> > > > I have been working with Parscale for some time, and
>> > > > I was always anxious when the Newton Cycles (after
>> > > > the E-M Cycles converge) did not converge (actually
>> > > > usually diverge). This time, its the same story. The
>> > > > Newton Cycles diverge. When I fiddle with the
>> > > > settings, Parscale manages 2-3 cycles and then
>> > > > diverges again. Anyone knowing any tricks to make
>> > > this creature converge? >
>> > > > Jason
>> > > >
>> > > > ----- Original Message Follows -----
>> > > > From: Paul Barrett <[log in to unmask]>
>> > > > To: [log in to unmask]
>> > > > Subject: Very important paper on SEM modeling
>> > > > Date: Fri, 5 Jan 2007 13:50:22 +1300
>> > > > > Hello again
>> > > > >
>> > > > > Almost forgot - but I think this is a very
>> > > > > important and readable paper for anyone
>> > > > > contemplating using hierarchical factor models in
>> > > > > SEM ... It's clearly written, and that nested
>> > > > > (bifactor) model is a very nice way of modeling a
>> > > > general factor. I've used this myself recently ... >
>> > > > > Gignac, G. (2007) Multi-factor modeling in
>> > > > > individual differences research: Some
>> > > > > recommendations and suggestions. Personality and
>> > > > > Individual Differences, 42, 1 , 37-48.
>> > > > >
>> > > > > Abstract
>> > > > > This paper offers some commentary and
>> > > > > recommendations relevant the multi-factor modeling
>> > > > > in individual differences research. Several
>> > > > > similarities and distinctions between oblique
>> > > > > factor modeling, higherorder modeling,
>> > > > > Schmid-Leiman transformations, and nested factors
>> > > > > modeling are discussed. An empirical illustration
>> > > > > of the various multi-factor models is presented,
>> > > > > based on 18 items derived from three Neuroticism
>> > > > > facets within the NEO PI-R. Researchers are
>> > > > > encouraged to always perform a Schmid-Leiman
>> > > > > transformation to a higher-order model solution,
>> > > > > as well as to consider the possibility that a
>> > > > > nested factors model will yield superior model fit
>> > > > , in comparison to a higher-order model, as well as
>> > > > less ambiguous factor solutions. > >
>> > > > > Another recent paper on the same topic - but
>> > > > > focused more in the Quality of Life literature is:
>> > > > >
>> > > > > Chen, F.F., West, S.G., and Sousa, K.H. (2006) A
>> > > > > comparison of bifactor and second order models of
>> > > > > quality of life. Multivariate Behavioral Research,
>> > > > 41, 2, 189-225. >
>> > > > > Abstract
>> > > > > Bifactor and second-order factor models are two
>> > > > > alternative approaches for representing general
>> > > > > constructs comprised of several highly related
>> > > > > domains. Bifactor and second-order models were
>> > > > > compared using a quality of life data set (N =
>> > > > > 403). The bifactor model identified three, rather
>> > > > > than the hypothesized four, domain specific
>> > > > > factors beyond the general factor. The bifactor
>> > > > > model fit the data significantly better than the
>> > > > > second-order model. The bifactor model allowed for
>> > > > > easier interpretation of the relationship between
>> > > > > the domain specific factors and external variables
>> > > , over and above the general factor. Contrary to the
>> > > > > literature, sufficient power existed to
>> > > > > distinguish between bifactor and corresponding
>> > > > > second-order models in one actual and one
>> > > > > simulated example, given reasonable sample sizes.
>> > > > Advantages of bifactor models over second-order
>> > > > models are discussed. > >
>> > > > > Regards .. Paul
>> > > > >
>> > > > ___________________________________________________
>> > > > > > Paul Barrett
>> > > > > Mob: +64-021-415625 www.pbmetrix.com
>> > > > > <http://www.pbarrett.net/> Skype: pbar088
>> > > > > [log in to unmask]
>> > > > >
>> > > > >
>> > > >
>> > >
>> > >
>> > >
>> > > --
>> > > ***************
>> > > A. Alexander Beaujean, Ph.D.
>> > > http://myprofile.cos.com/abeaujean
>> > > http://www.baylor.edu/soe/faculty/index.php?id=38476
>> > >
>> > >
>> > >
>> > > "General impressions are never to be trusted.
>> > > Unfortunately when they are of long standing they
>> > > become fixed rules of life, and assume a prescriptive
>> > > right not to be questioned. Consequently those who are
>> > > not accustomed to original inquiry entertain a hatred
>> > > and a horror of statistics. They cannot endure the
>> > > idea of submitting their sacred  impressions to
>> > > cold-blooded verification. But it is the triumph of
>> > > scientific men to rise superior to such superstitions,
>> > > to devise tests by which the value of beliefs may be
>> > > ascertained, and to feel sufficiently masters of
>> > > themselves to discard contemptuously whatever may be
>> > > found untrue." --Sir Francis Galton, FRS
>> > >
>> >
>> 
>> 
>> 
>> -- 
>> ***************
>> A. Alexander Beaujean, Ph.D.
>> http://myprofile.cos.com/abeaujean
>> http://www.baylor.edu/soe/faculty/index.php?id=38476
>> 
>> 
>> 
>> "General impressions are never to be trusted.
>> Unfortunately when they are of long standing they become
>> fixed rules of life, and assume a prescriptive right not
>> to be questioned. Consequently those who are not
>> accustomed to original inquiry entertain a hatred and a
>> horror of statistics. They cannot endure the idea of
>> submitting their sacred  impressions to cold-blooded
>> verification. But it is the triumph of scientific men to
>> rise superior to such superstitions, to devise tests by
>> which the value of beliefs may be ascertained, and to feel
>> sufficiently masters of themselves to discard
>> contemptuously whatever may be found untrue." --Sir
>> Francis Galton, FRS
>> 
>

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