Journal Article

Some t-tests for N-of-1 trials with serial correlation

Landes, Reid D., Tang, Jillian

2020

Overview

N-of-1 trials allow inference between two treatments given to a single individual. Most often, clinical investigators analyze an individual's N-of-1 trial data with usual t-tests or simple nonparametric methods. These simple methods do not account for serial correlation in repeated observations coming from the individual. Existing methods accounting for serial correlation require simulation, multiple N-of-1 trials, or both. Here, we develop t-tests that account for serial correlation in a single individual. The development includes effect size and precision calculations, both of which are useful for study planning. We then use Monte Carlo simulation to evaluate statistical properties of these serial t-tests, namely, Type I and II errors, and confidence interval widths, and compare these statistical properties to those of analogous usual t-test. The serial t-tests clearly outperform the usual t-tests commonly used in reporting N-of-1 results. Examples from N-of-1 clinical trials in fibromyalgia patients and from a behavioral health setting exhibit how accounting for serial correlation can change inferences. These t-tests are easily implemented and more appropriate than simple methods commonly used; however, caution is needed when analyzing only a few observations.

• Publisher: Public Library of Science,Public Library of Science (PLoS)
• Subject: Accounting / Amitriptyline - therapeutic use / Behavioral medicine / Cellular proteins / Clinical trials / Clinical Trials as Topic / Computer and Information Sciences / Computer simulation / Confidence intervals / Correlation / Fibromyalgia / Fibromyalgia - drug therapy / Humans / Maximum likelihood method / Medical research / Medicine and Health Sciences / Monte Carlo Method / Monte Carlo methods / Monte Carlo simulation / Opioid-Related Disorders - drug therapy / Physical sciences / Research and Analysis Methods / Researchers / Sample Size / Setting (Literature) / Statistical analysis / Statistics / Student's t-test / Studies / Test procedures / Time series