The Role of a PMI-Prediction Model in Evaluating Forensic Entomology Experimental Design, the Importance of Covariates, and the Utility of Response Variables for Estimating Time Since Death

• NCJ Number: 252445
• Author(s): Jeffrey Wells; Lynn LaMotte
• Date Published: 2017
• Length: 1 page
• Grant Number(s): 2002-LT-BX-K001; 2013-DN-BX-K042
• Agencies: NIJ-Sponsored
• Publication Type: Research (Applied/Empirical); Report (Study/Research); Report (Grant Sponsored); Program/Project Description
• Award: Statistical Methods for Combining Multivariate and Categorical Data in Postmortem Interval Estimation

Annotation

Using the authors' research on calculating postmortem interval (PMI) estimate probabilities, the current project indicates how training data experiment design can influence the performance of a statistical model for PMI prediction.

Abstract

The most common forensic entomological application is the estimation of some portion of the time since death, or postmortem interval (PMI). To the authors' knowledge, a PMI estimate is almost never accompanied by an associated probability. Statistical methods are now available for calculating confidence limits for an insect-based prediction of PMI for both succession and development data. In addition to it now being possible to employ these approaches in validation experiments and casework, it is also now possible to use the criterion of prediction performance to guide training experiments, i.e., to modify carrion insect development or succession experiment design in ways likely to improve the performance of PMI predictions using the resulting data. (Publisher abstract modified)