Episode

KEYNOTE: Structural Equation Modeling: models, software and stories

with Yves Rosseel

In the social sciences, structural equation modeling (SEM) is often considered to be the mother of all statistical modeling. It includes univariate and multivariate regression models, generalized linear mixed models, factor analysis, path analysis, item response theory, latent class analysis, and much more. SEM can also handle missing data, non-normal data, categorical data,multilevel data, longitudinal data, (in)equality constraints, and on a good day, SEM makes you a fresh cup of tea.

For several decades, software for structural equation modeling was exclusively commercial and/or closed-source. Today, several free and open-source alternatives are available. In this presentation, I will tell the story of the R package `lavaan'. How was it conceived? What were the original goals, and where do we stand today? And why is it not finished yet? As the story unfolds, I will highlight some aspects of software development that are often underexposed: the importance of software archaeology, the design of model syntax, the importance of numerical techniques, the curse of backwards compatibility, the temptation to use compiled code to speed things up, and the difficult choice between a monolithic versus a modular approach.

Finally, I will talk about my experiences with useRs, discussion groups, community support and the lavaan ecosystem.