Combined Judgmental and Random Sampling for Items with Uniform Prior

This module is a special case of the Combined Judgmental and Random (CJR) sampling design, where the prior distribution is chosen to be uniform. The uniform distribution is a non-informative prior and gives results that are very similar to traditional frequentist (non-Bayesian) methods. The help page for the CJR design is still applicable, except \(P_J\) is set to 0.50, which implies \(\beta\) = 1, and consequently, \(\theta\) follows a uniform distribution on the interval (0,1).

This module uses terminology and visualizations adapted to sampling of discrete items rather than sampling grid cells on surfaces.

This dialog also contains the Item Arrangement page for controlling the visualization of the items.