Hi again
until i manage to use ltm in R, I would be greateful if
anyone knew how to fix the discrimination parameter of the
items to 1 in Parscale.
Jason
----- Original Message Follows -----
From: Iasonas Lamprianou <[log in to unmask]>
To: [log in to unmask]
Subject: Re: Parscale
Date: Tue, 16 Jan 2007 19:09:23 +0200
> 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]
> >
> >
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