title: A comparison of four methods for the analysis of N-of-1 trials.
abstract: OBJECTIVE
  To provide a practical guidance for the analysis of N-of-1 trials by comparing four commonly used models.
  
  
  METHODS
  The four models, paired t-test, mixed effects model of difference, mixed effects model and meta-analysis of summary data were compared using a simulation study. The assumed 3-cycles and 4-cycles N-of-1 trials were set with sample sizes of 1, 3, 5, 10, 20 and 30 respectively under normally distributed assumption. The data were generated based on variance-covariance matrix under the assumption of (i) compound symmetry structure or first-order autoregressive structure, and (ii) no carryover effect or 20% carryover effect. Type I error, power, bias (mean error), and mean square error (MSE) of effect differences between two groups were used to evaluate the performance of the four models.
  
  
  RESULTS
  The results from the 3-cycles and 4-cycles N-of-1 trials were comparable with respect to type I error, power, bias and MSE. Paired t-test yielded type I error near to the nominal level, higher power, comparable bias and small MSE, whether there was carryover effect or not. Compared with paired t-test, mixed effects model produced similar size of type I error, smaller bias, but lower power and bigger MSE. Mixed effects model of difference and meta-analysis of summary data yielded type I error far from the nominal level, low power, and large bias and MSE irrespective of the presence or absence of carryover effect.
  
  
  CONCLUSIONS
  We recommended paired t-test to be used for normally distributed data of N-of-1 trials because of its optimal statistical performance. In the presence of carryover effects, mixed effects model could be used as an alternative.
authors: Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, Guangdong province, China ; Department of Preventive Medicine and Biostatistics, College of fundamental Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong province, China.
authors: Xinlin
authors: X
authors: Chen
authors: Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, Guangdong province, China.
authors: Pingyan
authors: P
authors: Chen
mesh_terms: D000465:Algorithms; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic; D012107:Research Design