Finite mixture factor analysis provides a parsimonious model to explore latent group structures of high-dimensional data. In this modeling framework, we can explore latent structures for continuousâ€¦ (More)

Item response theory (IRT) is concerned with accurate test scoring and development of test items. You design test items to measure various kinds of abilities (such as math ability), traits (such asâ€¦ (More)

High-dimensional longitudinal data involving latent variables such as depression and anxiety that cannot be quantified directly are often encountered in biomedical and social sciences. Multipleâ€¦ (More)

Researchers often use longitudinal data analysis to study the development of behaviors or traits. For example, they might study how an elderly personâ€™s cognitive functioning changes over time or howâ€¦ (More)

The item factor analysis model for investigating multidimensional latent spaces has proved to be useful. Parameter estimation in this model requires computationally demanding high-dimensionalâ€¦ (More)