An important step when designing an empirical study is to justify the sample size that will be
collected. The key aim of a sample size justification for such studies is to explain how the …

Bringing precision to the understanding and treatment of mental disorders requires
instruments for studying clinically relevant individual differences. One promising approach is …

Identifying brain biomarkers of disease risk is a growing priority in neuroscience. The ability
to identify meaningful biomarkers is limited by measurement reliability; unreliable measures …

It has recently been demonstrated that metrics of structural validity are severely
underreported in social and personality psychology. We comprehensively assessed …

Emotion researchers that use experience sampling methods (ESM) study how emotions
fluctuate in everyday life. To reach valid conclusions, confirming the reliability of momentary …

Cognitive tasks are capable of providing researchers with crucial insights into the
relationship between cognitive processing and psychiatric phenomena. However, many …

Bien qu'il soit certain que de nombreux facteurs contribuent à la crise de la reproductibilité
en psychologie, l'un d'entre eux, largement méconnu, est la négligence des principes de …

Estimating the reliability of cognitive task datasets is commonly done via split-half methods.
We review four methods that differ in how the trials are split into parts: a first-second half …

Infant research is often underpowered, undermining the robustness and replicability of our
findings. Improving the reliability of infant studies offers a solution for increasing statistical …

The R package splithalf provides tools to estimate the internal consistency reliability of
cognitive measures. In particular, the tools were developed for application to tasks that use …