Jillian Tang
Masters Student in Computer Science, admitted Autumn 2019
Student Employee, Computer Science
All Publications
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Some t-tests for N-of-1 trials with serial correlation
PLOS ONE
2020; 15 (2): e0228077
Abstract
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.
View details for DOI 10.1371/journal.pone.0228077
View details for Web of Science ID 000534618100013
View details for PubMedID 32017772
View details for PubMedCentralID PMC6999905