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lecture1_s10 preliminaries

# lecture1_s10 preliminaries - Covariance structure and...

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Covariance structure and factor models PSYC/EPSY/SOC/STAT 588 Spring 2010 Instructor: Sungjin Hong Office: Psych 429 (244-8296, hongsj AT illinois DOT edu) Class meetings: WF, 12:00-1:50, room 29 (219A to access AMOS; 219A also reserved for Tue 3-5) Office hours: W, 2:00-3:00 or by appointment Course website: https://netfiles.uiuc.edu/hongsj/shared/psy588

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Historical backgrounds 1. Path analysis 2. Factor analysis (measurement model in SEM terms) 3. General estimation procedure
1. Path analysis • To parsimoniously describe relationships between a set of observed variables with directed paths by which we wish to represent causal influences of one variable to another IQ AI GPA ab E G E A () ( ) GA 2 G GPA IQ E , AI GPA E cov GPA,AI var IQ var E b =+ = +

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2. Factor analysis • Scientifically useful variables are often not directly observable (measurable) --- e.g., IQ • FA defines the unobservable (latent) variables such that they linearly relate to (influence or determine) a set of correlated, yet distinctive, observable variables (indicators) 11 1 1 IQ qq q q X ab E X E =+ + + ## # 2 2 . cf c X c X c X E + + + " IQ IQ
3. General estimation procedure

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lecture1_s10 preliminaries - Covariance structure and...

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