It is well known in statistics and machine learning that the combination of latent (or hidden) variables and observed variables offer more expressive power than models with observed variables alone. Latent variables

This article examines the theoretical status of latent variables as used in modern test theory models. First, it is argued that a consistent interpretation of such models requires a realist ontology for latent variables. Second, the relation between latent variables and their indicators

) normative belief, f) risk perception as measured by subjective probability and consequence estimates of major disasters including earthquakes, g) a disaster schema that guides individuals to construct certain phenomena as disasters, h) resources available to individuals, and i) socio-demographic variables

additive latent variable models

Classical test theory Congeneric test theory 2 Reliability and internal structure Estimating reliability by split halves

This individual differences study examined the separability of three often postulated executive functions—mental set shifting ("Shifting"), information updating and monitoring ("Updating"), and inhibition of prepotent responses ("Inhibition")—and their roles in complex "frontal lobe" or "executive" tasks. One hundred thirty-seven college students performed a set of relatively simple experimental tasks that are considered to predominantly tap each target executive function as well as a set of frequently used executive tasks: the Wisconsin Card Sorting Test (WCST), Tower of Hanoi (TOH), random number generation (RNG), operation span, and dual tasking. Confirmatory factor analysis indicated that the three target executive functions are moderately correlated with one another, but are clearly separable. Moreover, structural equation modeling suggested that the three functions

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formalism This chapter gives the theoretical basis for continuous latent variable models. Section 2.1 defines intuitively the concept of latent variable models and gives a brief historical introduction to them. Section 2.2 uses a simple example, inspired by the mechanics of a mobile point

Abstract. A powerful approach to probabilistic modelling involves supplementing a set of observed variables with additional latent, or hidden, variables. By defining a joint distribution over visible and latent variables, the corresponding distribution of the observed variables is then obtained

continuous variable, and another in which democracy is operationalized a latent class. We show how tobetter exploit the information in thePolity data set so as to produce amore reliable scale measure (or classification) of democracy. Our modeling approaches also let us assess the ‘‘noise’ ’ (measurement