Abstract
ABSTRACTN-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers’ access to robust and user-friendly statistical methods for individualised studies.
Highlights
Between-participant studies, such as cohort studies or randomised controlled trials (RCTs), are the most prevalent research study designs, whether the aim is to identify predictors of response or estimate the population-level effect of an intervention
Dynamic modelling accounts for the effect of past on the future by including lagged variables representing the past history of the predictors and outcome in an otherwise conventional multiple regression model
The analysis showed that if the process is dynamic, i.e., if there is an effect of the past on the current values of the process being studied, the estimates provided by the dynamic model were superior to the other models or estimators, even in the presence of a weak effect
Summary
Between-participant studies, such as cohort studies or randomised controlled trials (RCTs), are the most prevalent research study designs, whether the aim is to identify predictors of response or estimate the population-level effect of an intervention. It is essential to acknowledge that n-of-1 data have a time-series structure and that autocorrelation, if present, needs to be accounted for when considering statistical analysis.
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