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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

The most common forensic entomological application is the estimation of some portion of the time since death, or postmortem interval (PMI). To our knowledge, a PMI estimate is almost never accompanied by an associated probability. Statistical methods are now available for calculating confidence limi...

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Detalles Bibliográficos
Autores principales: Wells, Jeffrey, LaMotte, Lynn
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5492061/
http://dx.doi.org/10.3390/insects8020047
Descripción
Sumario:The most common forensic entomological application is the estimation of some portion of the time since death, or postmortem interval (PMI). To our 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. In this paper, we provide examples, derived from our research program on calculating PMI estimate probabilities, of how training data experiment design can influence the performance of a statistical model for PMI prediction.