Abstract

Two applications are described of a probability model that can express uncertainty regarding a pre-specified monotonicity hypothesis for binomial proportions. The model also yields a random effects overdispersion formulation where the population proportions definitely satisfy a monotonicity specification. One application concerns an insurance data set recording mortalities of clients from ages 35 to 64. Two new actuarial graduation procedures are developed. The other application derives from a Veterans' administration hospital quality monitor and concerns the failure to return rates for psychiatric patients attending substance abuse clinics. While smoothed performance indicators are proposed, measures of their extra-binomial variation highlight problems experienced by evidence-based approaches when the data are uncontrolled.

This work is licensed under a Creative Commons Attribution 4.0 License.