A1709
Title: Statistical analysis of data from supersaturated split-plot experiments
Authors: Zhuowei Liang - Kings College London (United Kingdom) [presenting]
Kalliopi Mylona - King's College London (United Kingdom)
Abstract: The supersaturated split-plot designs (SSPDs) are screening designs that have more potentially active factors than the number of experimental units under restricted randomisation due to the presence of hard-to-change factors. SSPDs reduce the experimental cost drastically, however, conventional statistical analysis methods are not applicable due to the large p small n feature and the random effect induced by restricted randomisation makes the data analysis even more challenging. We will present a Bayesian method for analysing data from SSPD experiments.
