Some t-tests for N-of-1 trials with serial correlation
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 evaluate and compare their Type I and II errors and interval estimators to those of usual t-tests analogues via Monte Carlo simulation. 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. Keywords: Autocorrelation; Cross-over studies; Repeated measures analysis; Single-case experimental design; Time-series
- Publication:
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PLoS ONE
- Pub Date:
- February 2020
- DOI:
- 10.1371/journal.pone.0228077
- arXiv:
- arXiv:1904.01622
- Bibcode:
- 2020PLoSO..1528077T
- Keywords:
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- Statistics - Methodology
- E-Print:
- 23 pages, 6 figures, 6 tables