Here - Tilburg University

The ASA Spring Methodology Conference
Organized in Europe by the Department of Methodology and Statistics at Tilburg
University, the Netherlands.
SESSION: Applications of Latent Variable Models
SUMMARY
For many constructs of interest in the social sciences, educational
measurement, psychology, biology, and economics, no direct method exists for
measurement. Nonetheless, examples of such constructs are legion, for instance
think of political attitudes, abilities, personal traits, or product preferences. To
get a hold of such constructs, researchers gather observable variables (hereafter
called indicators, manifest variables, or items) which they hope will provide
indirect evidence for the constructs of interest. Latent variable models are
statistical models built to quantify and help objectify this type of inference by
deriving a small set of latent unobserved variables that is underlying to the set
of manifest variables and should reflect the constructs of interest. Well-known
instances of this type of modeling approach are factor analysis (Thurstone,
1947), latent class and latent profile analysis (Lazarsfeld & Henry, 1968), and
item response theory (Lord & Novick, 1968).
Although the foundations of latent variable models were laid several years
ago, it has taken quite some time before they became widely applied. This is
mainly due to the statistical nature of these models as well as the sometimes
complicated computations and algorithms needed to estimate latent variable
models. With the recent advances in computation speed and optimization
algorithms and the availability of general purpose software able to fit latent
variable models, this has become less of an issue.
This session is intended as a brief showcase of the possibilities that a
latent variable model framework can offer for research in the social and
behavioral sciences. Each presentation will fill in and illustrate one of the most
familiar model instances in the framework (see Figure).