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Re: st: Query..


From   John Antonakis <John.Antonakis@unil.ch>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: Query..
Date   Tue, 16 Apr 2013 19:51:10 +0200

In general I find Acock's books helpful and I have bought two of them. The latest one he has on SEM was gives a very nice overview of the SEM module in Stata. However, it is disappointing on some of the statistical theory, in particular with respect to fact that he gave too much coverage to "approximate" indexes of overidentification, which are not tests, and did not explain enough what the chi-square statistic of overidentification is.

The Stata people are usually very good about strictly following statistical theory, as do all econometricians, and do not promote too much these approximate indexes. So, I was a bit annoyed to see how much airtime was given to rule-of-thumb indexes that have no known distributions and are not tests. The only serious test of overidentification, analogous to the Hansen-Sargen statistic is the chi-square test of fit. So, my suggestion to Alan is that he spends some time to cover that in the updated addition and not to suggest that models that fail the chi-square test are "approximately good."

For those who do not know what this statistic does, it basically compares the observed variance-covariance (S) matrix to the fitted variance covariance matrix (sigma) to see if the difference (residuals) are simultaneously different from zero. The fitting function that is minimized is:

Fml =  ln|Sigma| - ln|S| + trace[S.Sigma^-1] - p

As Sigma approaches S, the log of the determinant of Sigma less the log of the determinant of S approach zero; as concerns the two last terms, as Sigma approaches S, the inverse of Sigma premultiplied by S makes an identity matrix, whose trace will equal the number of observed variables p (thus, those two terms also approach zero). The chi-square statistic is simply Fml*N, at the relevant DF (which is elements in the variance-covariance matrix less parameters estimated).

This chi-square test will not reject a correctly specified model; however, it does not behave as expected at small samples, when data are not multivariate normal, when the model is complex (and the n to parameters estimated ration is low), which is why several corrections have been shown to better approximate the true chi-square distribution (e.g., Swain correction, Yuan-Bentler correction, Bollen-Stine bootstrap).

In all, I am thankful to Alan for his nice "how-to" guides which are very helpful to students who do not know Stata need a "gentle introduction"--so I recommend them to my students, that is for sure. But, I would appreciate a bit more beef from him for the SEM book in updated versions.

Best,
J.

__________________________________________

John Antonakis
Professor of Organizational Behavior
Director, Ph.D. Program in Management

Faculty of Business and Economics
University of Lausanne
Internef #618
CH-1015 Lausanne-Dorigny
Switzerland
Tel ++41 (0)21 692-3438
Fax ++41 (0)21 692-3305
http://www.hec.unil.ch/people/jantonakis

Associate Editor
The Leadership Quarterly
__________________________________________

On 16.04.2013 17:45, Lachenbruch, Peter wrote:
> David -
> It would be good for you to specify what you find problematic with Acock's book. I've used it and not had any problems - but maybe i'm just ancient and not seeing issues
>
> Peter A. Lachenbruch,
> Professor (retired)
> ________________________________________
> From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Hutagalung, Robert [Robert.Hutagalung@med.uni-jena.de]
> Sent: Monday, April 15, 2013 2:06 AM
> To: statalist@hsphsun2.harvard.edu
> Subject: AW: st: Query..
>
> Hi David,
> Thanks, though I find the book very useful.
> Best, Rob
>
> -----Ursprüngliche Nachricht-----
> Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von David Hoaglin
> Gesendet: Samstag, 13. April 2013 16:11
> An: statalist@hsphsun2.harvard.edu
> Betreff: Re: st: Query..
>
> Hi, Rob.
>
> I am not able to suggest a book on pharmacokinetics/pharmacodynamics,
> but I do have a comment on A Gentle Introduction to Stata. As a statistician, I found it helpful in learning to use Stata, but a number of its explanations of statistics are very worrisome.
>
> David Hoaglin
>
> On Fri, Apr 12, 2013 at 9:01 AM, Hutagalung, Robert <Robert.Hutagalung@med.uni-jena.de> wrote:
>> Hi everyone, I am a new fellow here..
>> I am wondering if somebody could a book (or books) on Stata dealing with pharmacokinetics/pharmacodinamics - both analyses and graphs. >> I already have: A Visual Guide to Stata Graphics, 2' Edition, A Gentle Introduction to Stata, Third Edition, An Introduction to Stata for Health Researchers, Third Edition.
>> Thanks in advance, Rob.
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