Virtual StatsPD@Waite meeting

Every month, the professional development meetings of statisticians and data scientists at Waite, known as StatsPD@Waite, bring together specialists in various aspects of data sciences in agriculture from Waite, Roseworthy and Adelaide.

Please join us for the next StatsPD@Waite seminar where Omer Ozturk from the Ohio State University will present on his collaborative work on the cluster randomized ranked designs.

Also please note that the StatsPD@Waite meetings are recorded. If you have a question to the speaker but had rather not be recorded, please send me your question via chat during the meeting and I will ask it on your behalf.

Please email Beata Sznajder for details of the Zoom meeting.

Title: Cluster Randomized Ranked Designs

Presenter: Omer Ozturk, Richard Jarret, Olena Kravchuk

Cluster randomized designs (CRD) provide a rigorous development for randomization principles for studies where treatments are allocated to cluster units rather than the individual subjects within clusters. It is known that CRDs are less efficient than completely randomized designs since the randomization of treatment allocation is applied the cluster units. To mitigate this problem, we embed ranked set sampling design from survey sampling studies into CRD for the selection of cluster and subsampling units. We show that ranking groups in ranked set sampling act like a covariate, reducing the expected mean squared cluster error and increasing the precision of the sampling design. We provide an optimality result to determine the sample sizes at cluster and sub-sample level. We apply the proposed sampling design to a longitudinal study from an education intervention program. We also provide an example where order restricted cluster randomized design would be appropriate in field experiments.