Sample size calculations for n-of-1 trials

by   Jiabei Yang, et al.

N-of-1 trials, single participant trials in which multiple treatments are sequentially randomized over the study period, can give direct estimates of individual-specific treatment effects. Combining n-of-1 trials gives extra information for estimating the population average treatment effect compared with randomized controlled trials and increases precision for individual-specific treatment effect estimates. In this paper, we present a procedure for designing n-of-1 trials. We formally define the design components for determining the sample size of a series of n-of-1 trials, present models for analyzing these trials and use them to derive the sample size formula for estimating the population average treatment effect and the standard error of the individual-specific treatment effect estimates. We recommend first finding the possible designs that will satisfy the power requirement for estimating the population average treatment effect and then, if of interest, finalizing the design to also satisfy the standard error requirements for the individual-specific treatment effect estimates. The procedure is implemented and illustrated in the paper and through a Shiny app.



There are no comments yet.


page 1

page 2

page 3

page 4


Estimating heterogeneous treatment effects in nonstationary time series with state-space models

Randomized trials and observational studies, more often than not, run ov...

Power Analysis for Stepped Wedge Trials with Two Treatments

Stepped wedge designs (SWDs) are designs for cluster randomized trials t...

Designing efficient randomized trials: power and sample size calculation when using semiparametric efficient estimators

Trials enroll a large number of subjects in order to attain power, makin...

Analysis of stepped wedge cluster randomized trials in the presence of a time-varying treatment effect

Stepped wedge cluster randomized controlled trials are typically analyze...

Regression discontinuity design: estimating the treatment effect with standard parametric rate

Regression discontinuity design models are widely used for the assessmen...

A Matching Procedure for Sequential Experiments that Iteratively Learns which Covariates Improve Power

We propose a dynamic allocation procedure that increases power and effic...

Optimal Design in Hierarchical Models with application in Multi-center Trials

Hierarchical random effect models are used for different purposes in cli...

Code Repositories

This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.