With recent advances in sequencing, genotyping arrays, and imputation, GWAS now aim to identify associations with rare and uncommon genetic variants. Here, we describe and evaluate a class of ...

The books Lies, Damn Lies, and Statistics (Wheeler, 1976) and Damned Lies and Statistics (Best, 2001) have raised questions about whether statistics can be trusted. A number of educated people today, ...

Significance testing, with appropriate multiple testing correction, is currently the most convenient method for summarizing the evidence for association between a disease and a genetic variant.

The power of genome-wide association studies (GWAS) to detect genetic influences on human disease can be substantially increased using a statistical testing framework. Despite the proliferation of ...

Statistical significance is a critical concept in data analysis and research. In essence, it’s a measure that allows researchers to assess whether the results of an experiment or study are due to ...

Post-hoc testing is carried out after a statistical analysis where you have performed multiple significance tests, ‘post-hoc’ coming from the Latin “after this”. Post-hoc analysis represents a way to ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...