Lecture

Choice models with latent variables: Modeling latent concepts

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Description

This lecture covers choice models with latent variables, focusing on modeling latent concepts. It discusses indirect measurements of latent concepts such as perception of transportation mode and attitude towards the environment. The lecture also explains psychometric indicators and the challenges of using them as explanatory variables. Finally, it delves into modeling latent concepts, defining latent variables and their relation to observed variables.

In MOOC

Selected Topics on Discrete Choice

The logit model is the workhorse of choice modelers. But it has some limitations. In particular, some assumptions used to derive it may not be consistent with the behavioral reality. It may lead to erroneous forecast. We illustrated using the so-called "red bud-blue bus" paradox, and Multivariate Extre Value models, addressing some of these issues, are introduced. The sampling procedure used to collect choice data has a critical impact on the model estimation procedure. We introduce classical sampling proc

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Related concepts (17)

Latent variable model

A latent variable model is a statistical model that relates a set of observable variables (also called manifest variables or indicators) to a set of latent variables. It is assumed that the responses on the indicators or manifest variables are the result of an individual's position on the latent variable(s), and that the manifest variables have nothing in common after controlling for the latent variable (local independence).

Latent and observable variables

In statistics, latent variables (from Latin: present participle of lateo, “lie hidden”) are variables that can only be inferred indirectly through a mathematical model from other observable variables that can be directly observed or measured. Such latent variable models are used in many disciplines, including political science, demography, engineering, medicine, ecology, physics, machine learning/artificial intelligence, bioinformatics, chemometrics, natural language processing, management, psychology and the social sciences.

Psychometrics

Psychometrics is a field of study within psychology concerned with the theory and technique of measurement. Psychometrics generally refers to specialized fields within psychology and education devoted to testing, measurement, assessment, and related activities. Psychometrics is concerned with the objective measurement of latent constructs that cannot be directly observed. Examples of latent constructs include intelligence, introversion, mental disorders, and educational achievement.

Structural equation modeling

Structural equation modeling (SEM) is a diverse set of methods used by scientists doing both observational and experimental research. SEM is used mostly in the social and behavioral sciences but it is also used in epidemiology, business, and other fields. A definition of SEM is difficult without reference to technical language, but a good starting place is the name itself. SEM involves a model representing how various aspects of some phenomenon are thought to causally connect to one another.

Rational choice theory

Rational choice theory refers to a set of guidelines that help understand economic and social behaviour. The theory originated in the eighteenth century and can be traced back to political economist and philosopher, Adam Smith. The theory postulates that an individual will perform a cost-benefit analysis to determine whether an option is right for them. It also suggests that an individual's self-driven rational actions will help better the overall economy. Rational choice theory looks at three concepts: rational actors, self interest and the invisible hand.

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