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• W816857100 abstract "The focus of this chapter is almost exclusively on statistical issues and procedures commonly employed in cultivation-dependent approaches to microbial source tracking (MST), and the material in the chapter is also relevant more broadly. A section presents a critical review of statistical techniques for discriminant analysis in microbial source tracking. In the context of microbial source tracking, multidimensional scaling (MDS) plots are based on a matrix of numerical interisolate dissimilarity measures. Statistical methods for predictive discriminant analysis are commonly referred to as classification rules. This section describes the general process of constructing and evaluating classification rules in the context of microbial source tracking. The three most common types of similarity-based rules in the source-tracking literature are the maximum-similarity, average-similarity, and k-nearest-neighbor rules. Most of the techniques and tools for discriminant analysis discussed in the chapter require software for implementation. It is likely that SAS is used more often than other packages because of its wide availability and flexibility. The chapter reviews current statistical practice in microbial source tracking with particular attention to evaluation of method performance, sampling considerations, and discriminant analysis. Lastly, methods for addressing exploratory, confirmatory, and predictive discriminant analysis are presented. Recent ad hoc procedures to evaluate and improve the reliability of source identifications are also discussed. However, the development of valid measures of reliability and confidence in source identifications is an important problem requiring further statistical research." @default.
• W816857100 created "2016-06-24" @default.
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• W816857100 date "2014-04-30" @default.
• W816857100 modified "2023-09-22" @default.
• W816857100 title "Statistical Issues in Microbial Source Identification" @default.
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• W816857100 doi "https://doi.org/10.1128/9781555815769.ch6" @default.
• W816857100 hasPublicationYear "2014" @default.
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