Multivariate Probability of Detection Modeling Including Categorical Variables and Higher-Order Response Models

This paper presents a methodology for extending probability of detection (POD) modeling for continuously valued (â vs. a) signal responses to allow for the addition of multiple variables beyond the simple discontinuity size model, along with higher-level interactions. The statistical methodology for correctly transforming these more complex linear models into POD curves is provided, and the approach is illustrated with a simulated dataset that includes polynomial and categorical predictors.