Despite much criticism, black-or-white null-hypothesis significance testing with an arbitrary P-
value cutoff still is the standard way to report scientific findings. One obstacle to progress is …

Computational social science is more than just large repositories of digital data and the
computational methods needed to construct and analyse them. It also represents a …

Doing Meta-Analysis with R: A Hands-On Guide serves as an accessible introduction on
how meta-analyses can be conducted in R. Essential steps for meta-analysis are covered …

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 …

Most theories and hypotheses in psychology are verbal in nature, yet their evaluation
overwhelmingly relies on inferential statistical procedures. The validity of the move from …

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 …

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 …

There has been a focus on autistic-led and participatory research in autism research, but
minimal discussion about whether the field is hospitable to autistic involvement. While the …

We discuss problems the null hypothesis significance testing (NHST) paradigm poses for
replication and more broadly in the biomedical and social sciences as well as how these …

Bayesian parameter estimation and Bayesian hypothesis testing present attractive
alternatives to classical inference using confidence intervals and p values. In part I of this …