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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 >> >