The dominant paradigm for inference in psychology is a null-hypothesis significance testing
one. Recently, the foundations of this paradigm have been shaken by several notable …

Traditional methods of analyzing data from psychological experiments are based on the
assumption that there is a single random factor (normally participants) to which …

While outlining his vision of The New Statistics, Cumming (2014) proposes that a more
rigorous and cumulative psychological science will be built, in part, by having psychologists …

Running studies with high statistical power, while effect size estimates in psychology are
often inaccurate, leads to a practical challenge when designing an experiment. This …

Multiple baseline designs—both concurrent and nonconcurrent—are the predominant
experimental design in modern applied behavior analytic research and are increasingly …

In the January 2022 issue of Perspectives, Götz et al. argued that small effects are “the
indispensable foundation for a cumulative psychological science.” They supported their …

This practical guide explains the use of randomization tests and provides example designs
and macros for implementation in IBM SPSS and Excel. It reviews the theory and practice of …

Psychology has been embroiled in a professional crisis as of late. The research methods
commonly used by psychologists, especially the statistical analyses used to analyze …

The sample size necessary to obtain a desired level of statistical power depends in part on
the population value of the effect size, which is, by definition, unknown. A common approach …

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis
significance testing (NHST) paradigm to facilitate the design of informative experiments. In …