A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. Identifying causal relationships from observational data is not easy. Still, ...

The main focus of this course will be on linear mixed models. That is, linear models with fixed effects and random effects. Some topics we’ll discuss are: When would I want to use a random effect? How ...

For any analysis-of-variance model with balanced data involving both fixed and random effects, uniformly most powerful unbiased (UMPU) and uniformly most powerful invariant unbiased (UMPIU) tests are ...

Disease-mapping models for areal data often have fixed effects to measure the effect of spatially varying covariates and random effects with a conditionally antoregressive (CAR) prior to account for ...

Data may exhibit dependencies for many reasons. If a patient’s medical condition is measured across several time points, it seems unlikely that these measurements are totally unrelated. Educational ...

Mixed-effects location scale models represent a powerful statistical framework designed to investigate longitudinal data. By simultaneously modelling the mean trajectories (location) and residual ...