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.

High-dimensional statistical testing and covariance analysis constitute a rapidly evolving field that addresses the challenges inherent in analysing datasets where the number of variables often ...

Chapter 5 argued that substantial improvements in the cost-effectiveness of operational testing can be achieved by test planning and state-of-the-art statistical methods for test design. It was also ...

NOTICE: The project that is the subject of this report was approved by the Governing Board of the National Research Council, whose members are drawn from the councils of the National Academy 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 ...

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, ...

A study has validated a new statistical model that uses multiple standardized test scores over time to predict future academic performance. The dynamic measurement model accurately predicted academic ...