  Single subject or n-of-1 research designs have been widely used to evaluate
treatment interventions. Many statistical procedures such as split-middle trend
lines, regression trend line, Shewart-chart trend line, binomial tests,
randomization tests and Tryon C-statistics have been used to analyze
single-subject data, but they fail to control Type I error due to
serially-dependent time-series observations. The interrupted time series
analysis maintains Type I error but assumes that the intervention effect to be
a linear trend change from baseline. In this paper, we consider an improved
intervention analysis model (Box and Tiao, 1975) for dynamic characteristics of
an intervention effect in a short series of single-subject data. The maximum
likelihood estimates are derived and a hypothesis testing procedure is
proposed. The method is illustrated with a real clinical trial on constraint
induced language therapy for aphasia patients.
