Representing variables in the latent space

Latent variables in econometrics

Unobservable variables in econometrics are represented in one of three ways: by variables contaminated by measurement errors, by proxy variables, or by various manifest indicators and/or causes. This paper contains a discussion of models involving each of these representations, and highlights certain interesting implications that have been ‘insufficiently emphasized or completely unrecognized i...

State Space Techniques in Structural Equation Modeling Transformation of latent variables in and out of latent variable models

Representing Documents via Latent Keyphrase Inference

Many text mining approaches adopt bag-of-words or n-grams models to represent documents. Looking beyond just the words, i.e., the explicit surface forms, in a document can improve a computer's understanding of text. Being aware of this, researchers have proposed concept-based models that rely on a human-curated knowledge base to incorporate other related concepts in the document representation....

The theoretical status of 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 is discussed. It is maintained that this relation can be interpreted as a causal one but that in measurement ...

Concomitant Variables in Latent Change Models

A basic tenet in modeling preference behavior is that individuals differ in the ways they perceive and evaluate choice options. Latent-class analysis provides a parsimonious and flexible approach to represent these taste differences. This method decomposes a heterogeneous population of decision-makers into several homogeneous classes or subpopulations. Each decision-maker is assigned to one of ...