Latent variable modeling comprises a suite of methodologies that infer unobserved constructs from observable indicators, thereby enabling researchers to quantify abstract phenomena across diverse ...

This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual ...

In finance, data is often incomplete because the data is unavailable, inapplicable or unreported. Unfortunately, many classical data analysis techniques — for instance, linear regression — cannot ...

Following Cox & Wermuth (1994, 2002), we show that the distribution of a set of binary observable variables, induced by a certain discrete latent variable model, may be approximated by a quadratic ...

Social statistics is concerned with the development of statistical methods that can be used across the social sciences. Statisticians play an essential role in all aspects of social inquiry, including ...

This webpage provides information about the research project “Methods for the Analysis of Longitudinal Dyadic Data, with Applications to Intergenerational Exchanges of Family Support”. The three-year ...