BISC Seminar Announcement, August 16th, 1-2pm

Frank Hoffmann (fhoffman@cs.berkeley.edu)
Sat, 14 Aug 1999 11:07:41 +0200 (MET DST)

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Berkeley Initiative in Soft Computing (BISC)
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B I S C S e m i n a r A n n o u n c e m e n t
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The Moderation of Latent Regressive Relationships:
Modeling and Efficient Estimation

Speaker :
Andreas Klein
Psychology Department,
J.W.Goethe University Frankfurt, Germany
E-mail: a.klein@psych.uni-frankfurt.de

!!!!!!!!!!!!!!Note the seminar is on a Monday and from 12-pm !!!!!!!!!!!!!!!!!

Date: Monday, August 16th, 1999
Time: 1-2pm
Location : 508 Soda Hall

Abstract

In a structural equation, which represents a latent regressive
relationship, the latent variables are usually linearly related, that
is, the latent dependent variables are linear functions of the latent
independent variables. But in some cases theory may suggest that the
effect of a latent independent variable on a latent dependent variable
is itself moderated probabilistically by a second independent variable.
"MORE (you've seen 39%):"Then, in addition to the linear effects, a latent interaction effect
becomes part of the latent model structure. The interaction effect is
implemented by including a product of latent exogenous variables in the
structural equation. More general, latent interaction models involve
nonlinear structural relationships including one or several products of
exogenous variables in the structural equation. Therefore, latent
interaction models can be regarded as models which take the uncertainty
of a general relationship into account and, even more, a latent
uncertainty with overlaying measurement error.
In the LMS method, a stochastic analysis is carried out. LMS provides
efficient parameter estimates and yields unbiased standard errors for
inferential statistics. It outperforms alternative methods, e.g. LISREL
or 2SLS, with regard to generalizability, efficiency, statistical power,
and the capability of detecting latent interaction (Schermelleh-Engel,
Klein & Moosbrugger, 1998). Conclusions for the application of
interaction models under the methodological demands of substantive
matter research are drawn.

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Please direct questions with regard to the contents of the talk
and request for papers to the speaker.
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Frank Hoffmann UC Berkeley
Computer Science Division Department of EECS
Email: fhoffman@cs.berkeley.edu phone: 1-510-642-8282
URL: http://http.cs.berkeley.edu/~fhoffman fax: 1-510-642-5775
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