In basic neuroscience research, data are often clustered or collected with repeated
measures, hence correlated. The most widely used methods such as t test and ANOVA do …

The topic of centering in multilevel modeling (MLM) has received substantial attention from
methodologists, as different centering choices for lower-level predictors present important …

The concentration of dissolved oxygen in aquatic systems helps to regulate biodiversity,,
nutrient biogeochemistry, greenhouse gas emissions, and the quality of drinking water. The …

Statistics for Linguists: An Introduction Using R is the first statistics textbook on linear models
for linguistics. The book covers simple uses of linear models through generalized models to …

Microplastics contaminate environments worldwide and are ingested by numerous species,
whose health is affected in multiple ways. A key dimension of health that may be affected is …

When data are not normally distributed, researchers are often uncertain whether it is
legitimate to use tests that assume Gaussian errors, or whether one has to either model a …

Abstract The use of Linear Mixed-effects Models (LMMs) is set to dominate statistical
analyses in psychological science and may become the default approach to analyzing …

Large language models (LLMs) provide a new way to build chatbots by accepting natural
language prompts. Yet, it is unclear how to design prompts to power chatbots to carry on …

The brms package allows R users to easily specify a wide range of Bayesian single-level
and multilevel models, which are fitted with the probabilistic programming language Stan …

The integrated nested Laplace approximation (INLA) is a recent computational method that
can fit Bayesian models in a fraction of the time required by typical Markov chain Monte …