Kline, R. B. (in production). Get ready for data science: A primer for social and behavioral scientists. Guilford Press. Kline, R. B. (2023). Principles and practice of structural equation modeling ...

Structural equation modeling (SEM) encompasses such diverse statistical techniques as path analysis, confirmatory factor analysis, causal modeling with latent variables, and even analysis of variance ...

Consider fitting a linear equation to two observed variables, Y and X. Simple linear regression uses the model of a particular form, labeled for purposes of ...

This software specialises in three areas: models with responses at several levels of a data hierarchy, multilevel structural equation models, and measurement error ...

Latent factors are variables that cannot be observed directly but can be inferred from a set of observable variables. For example, in psychology, bad conduct (latent factor) can be measured by how ...

This course consists of two sections: Section 1 demonstrates linear regression to model the linear relationship between a response and predictor(s) when both the response and predictors are continuous ...

The CALIS procedure (Covariance Analysis and Linear Structural Equations) in SAS/STAT software estimates parameters and tests the appropriateness of linear structural equation models using covariance ...