28th International Congress of Psychology August 8 ... - U-netSURF

and stimulus salience. We conclude that reinforcement does not operate directly to select and/or
increase responses to stimuli or contexts but that it operates by the same mechanisms of salience
that impact most stimuli that are reliably paired in time. Subjects learn generally about salient
stimuli and events and the resources thereby availed to them as they strive for adaptation. (e.g.
paid) to do so.
5057 INVITED SYMPOSIUM
Advances in structural equation modeling
Convener and Chair: K.T. Hau, China
Co-convener: K.H. Yuan, USA
5057.1 Application of structural equation models in longitudinal study, C.P. Chou 1 , Y.I. Hser 2 ,
M.A. Pentz 1 , 1 University of Southern California, Alhambra, CA, USA; 2 University of California,
Los Angeles, CA, USA
Recently, SEM has been applied on multiple repeated measures in longitudinal studies. The
introduction of growth curve model and the utilization of SEM in parameter estimation make the
application of SEM in longitudinal study very appealing. The similarity of parameter estimates
between SEM and more commonly used statistical approaches for growth curve modeling, such as
hierarchical linear model, has demonstrated the equivalence of these two approaches in estimating
growth parameters. The SEM approach may, however, provide more information on model fitting
and more flexible model specification. A variety of structural equation models with empirical
results will be demonstrated.
5057.2 Comparing the statistical power of latent growth modeling analysis with other analytical
approaches, X. Fan, University of Virginia, Charlottesville, VA, USA
This paper examines the issue of statistical power in latent growth modeling (LGM) within the
framework of structural equation modeling in two kinds of situations: (a) in a one-group situation,
for detecting linear growth over repeated measurements, and (b) in a two-group situation, for
detecting group differences in latent growth trajectory parameters within the context of
quasi-experimental design with the assumption that the group difference may potentially occur in
both growth trajectory intercept and slope. Through the use of Monte Carlo simulation, the
statistical power of LGM described above is systematically and empirically compared with other
analytical approaches.
5057.3 Latent growth curve and interaction modeling: The case of travel mode choice, F. Yang
Wallentin 1 , P. Schmidt 2 , E. Davidov 3 , 1 Uppsala University, Uppsala, Sweden; 2 Institut für
Politikwissenschaften, Gießen, Germany; 3 Eldad Davidov, Cologne, Germany
In recent years, more scholars have tested interaction and non-linear effects in their models
including interaction effects between perceived-behavioral-control (PBC) and intention in the
theory of planned behavior. However, only a few applied structural equation modeling, and the
utility of latent growth modeling has largely remained unexplored. We compare
Maximum-Likelihood and Robustified ML to estimate the effect of the interaction of the slopes of
PBC and intention in the theory of planned behavior on the slope of the changing behavior over
1219