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

Jillian Tang and Reid D Landes

PLOS ONE, 2020, vol. 15, issue 2, 1-19

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.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0228077

DOI: 10.1371/journal.pone.0228077

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