Researchers face a tradeoff when applying latent variable models to time-series, cross-section*al data. Static models minimize bias but assume data are temporally independent, resulting in a loss of e
In latent variable models, interpretational confounding occurs when the inclusion of a covariate or outcome when fitting the model alters the results for the measurement model. Commonly used estimatio
Numerical models of atmosphere - ocean circulation are widely used to understand past climate and to project future climate change. Although the same laws of physics, chemistry,...
