Question

How are MRTs related to N-of-1 trials?

Answer

There are three key differences between MRTs and N-of-1 trials. The first is their inferential goals. MRTs are designed to provide data to test marginal causal effects. Marginal causal effects are effects that are averaged over the population (i.e. all individuals who are in recovery support), over a subset of the population (i.e. all young adults in recovery support) or over a subset of the population in a particular context (i.e. young adults in the morning on school days). The associated primary analyses, like most primary analyses in clinical trials, involve minimal assumptions. N-of-1 trials, on the other hand, are most often conducted to provide data to ascertain the most effective treatment for a particular individual. Here nuanced assumptions based on behavioral theory are used to conduct the primary analyses.

The second difference has to do with the types of interventions the trials were developed to optimize. MRTs are designed to help decide which of multiple intervention components should be included in a multi-component intervention, where N-of-1 trials were developed for settings in which scientists wish to compare the effect of one treatment to that of another (treatment package A versus treatment package B). Thus in the N-of-1 setting, repeated trials within an individual are usually scheduled at time points sufficiently far apart so that the assumption of no carry-over effects is valid. For example, when the individual is provided treatment (A), it is taken away, and then they are provided treatment (B), their previous exposure to treatment (A) does not affect their response to treatment (B). Or if this delayed effect might occur, the associated data analyses adjust for the carry-over effect. This makes eminent sense if the goal, as stated above, is to decide if for this individual it is better to provide treatment A or better to provide treatment B.

Third, MRTs provide data to inform the sequencing of treatments (intervention options)—that is to assist in constructing decision rules that indicate in which context, how soon after prior treatment and in what order different intervention options should be sequenced to be most effective. In  N-of-1 trials the usual goal is to compare one stand-alone treatment or treatment package versus another.

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