Bayesian statistics is an approach to data analysis based on Bayes' theorem, where
available knowledge about parameters in a statistical model is updated with the information …

Previous surveys of the literature have shown that reports of statistical analyses often lack
important information, causing lack of transparency and failure of reproducibility. Editors and …

The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled
“Missing data: Our view of the state of the art,” currently the most highly cited paper in the …

For almost half a century, Paul Meehl educated psychologists about how the mindless use of
null-hypothesis significance tests made research on theories in the social sciences basically …

A Tutorial on Conducting and Interpreting a Bayesian ANOVA in JASP | Cairn.info Cairn.info,
Matières à réflexion Cairn.info, Matières à réflexion Aucune suggestion trouvée Compte …

In small sample contexts, Bayesian estimation is often suggested as a viable alternative to
frequentist estimation, such as maximum likelihood estimation. Our systematic literature …

We illustrate the Bayesian approach to data analysis using the newly developed statistical
software program JASP. With JASP, researchers are able to take advantage of the benefits …

Applauded for its clarity, this accessible introduction helps readers apply multilevel
techniques to their research. The book also includes advanced extensions, making it useful …

This book introduces multiple-latent variable models by utilizing path diagrams to explain
the underlying relationships in the models. This approach helps less mathematically inclined …

In a frequentist framework, the exact fit of a structural equation model (SEM) is typically
evaluated with the chi-square test and at least one index of approximate fit. Current …