Detecting outliers in multivariate data while controlling false alarm rate
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چکیده
منابع مشابه
Detecting outliers in multivariate data while controlling false alarm rate
Outlier identification often implies inspecting each z-transformed variable and adding a Mahalanobis D2. Multiple outliers may mask each other by increasing variance estimates. Caroni & Prescott (1992) proposed a multivariate extension of Rosner’s (1983) technique to circumvent masking, taking sample size into account to keep the false alarm risk below, say, α = .05. Simulations studies here co...
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ژورنال
عنوان ژورنال: Tutorials in Quantitative Methods for Psychology
سال: 2012
ISSN: 1913-4126
DOI: 10.20982/tqmp.08.2.p108