Adaptive sampling in two-phase designs: a biomarker study for progression in arthritis

Response‐dependent two‐phase designs are used increasingly often in epidemiological studies to ensure sampling strategies offer good statistical efficiency while working within resource constraints. Optimal response‐dependent two‐phase designs are difficult to implement, however, as they require specification of unknown parameters. We propose adaptive two‐phase designs that exploit information from an internal pilot study to approximate the optimal sampling scheme for an analysis based on mean score estimating equations. The frequency properties of estimators arising from this design are assessed through simulation, and they are shown to be similar to those from optimal designs. The design procedure is then illustrated through application to a motivating biomarker study in an ongoing rheumatology research program. This is the peer-reviewed version of the following article: McIsaac, M. A., & Cook, R. J. (2015). Adaptive sampling in two-phase designs: a biomarker study for progression in arthritis. Statistics In Medicine, 34(21), 2899-2912. doi:10.1002/sim.6523, which has been published in final form at https://doi.org/10.1002/sim.6523. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions