Statistics for Sleep and Biological Rhythms Research

Author:

Bianchi Matt T.12,Phillips Andrew J. K.23,Wang Wei23,Klerman Elizabeth B.23

Affiliation:

1. Neurology Department, Massachusetts General Hospital, Boston, Massachusetts

2. Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts

3. Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, Massachusetts

Abstract

The Journal of Biological Rhythms will be publishing articles exploring analysis and statistical topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. By using case examples and highlighting the pearls and pitfalls of statistical inference, the authors will identify and explain ways in which experimental scientists can avoid common analytical and statistical mistakes and use appropriate analytical and statistical methods in their research. In this first article, we address the first steps in analysis of data: understanding the underlying statistical distribution of the data and establishing associative versus causal relationships. These ideas are then applied to sample size, power calculations, correlation testing, differences between description and prediction, and the narrative fallacy.

Publisher

SAGE Publications

Subject

Physiology (medical),Physiology

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Chemical modulation of circadian rhythms and assessment of cellular behavior via indirubin and derivatives;Chemical Tools for Imaging, Manipulating, and Tracking Biological Systems: Diverse Methods for Optical Imaging and Conjugation;2020

2. High Frequency Spectral Ultrasound Imaging to Detect Metastasis in Implanted Biomaterial Scaffolds;Annals of Biomedical Engineering;2019-09-23

3. Generalizability of A Neural Network Model for Circadian Phase Prediction in Real-World Conditions;Scientific Reports;2019-07-29

4. Analysis of Nonstationary Time Series for Biological Rhythms Research;Journal of Biological Rhythms;2017-06

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