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Bayesian methods are becoming increasingly used in applied psychological research. Previous researchers have thoroughly written about much of the details already, including the philosophy underlying Bayesian methods, computational issues associated with Bayesian model estimation, Bayesian model development and summary, and the role of Bayesian methods in the so‐called replication crisis. In this paper, we seek to provide case studies comparing the use of frequentist methods to the use of Bayesian methods in applied psychological research. These case studies are intended to 'illustrate by example' the ways that Bayesian modelling differs from frequentist modelling and the differing conclusions that one may arrive at using the two methods. The intended audience is applied psychological researchers who have been trained in the traditional frequentist framework, who are familiar with mixed‐effects models and who are curious about how statistical results might look in a Bayesian context. Along with our case studies, we provide general opinions and guidance on the use of Bayesian methods in applied psychological research. [ABSTRACT FROM AUTHOR]

An editorial is presented on the introduction of a special issue in the British Psychological Society (BPS) Journals, featuring papers centered around the theme of inequality in psychology. Topics include various aspects of inequality such as race, gender, and social class, with a commitment to promoting diversity and reducing discriminatory practices in the field.

An editorial is presented on the Editorial Advisory Group for the British Psychological Society (BPS) journals has delighted to present this special issue of landmark papers. Topics include the many different spheres of influence of psychological knowledge, the opportunity to delve outside of your immediate area of interest and read the whole spectrum of papers, and the emphasis on theoretical enhancement and of presenting theoretical interpretations of empirical findings.