| Literature DB >> 29969044 |
Fabrice I Mowbray1, Susan M Fox-Wasylyshyn1, Maher M El-Masri1.
Abstract
The presence of statistical outliers is a shared concern in research. If ignored or improperly handled, outliers have the potential to distort the estimate of the parameter of interest and thus compromise the generalizability of research findings. A variety of statistical techniques are available to assist researchers with the identification and management of outlier cases. The purpose of this paper is to provide a conceptual overview of univariate outliers with special focus on common techniques used to detect and manage univariate outliers. Specifically, this paper discusses the use of histograms, boxplots, interquartile range, and z-score analysis as common univariate outlier identification techniques. The paper also discusses the outlier management techniques of deletion, substitution, and transformation.Keywords: Outliers; management of outliers; outlier deletion; screening for outliers; substitution techniques; univariate outliers
Mesh:
Year: 2018 PMID: 29969044 DOI: 10.1177/0844562118786647
Source DB: PubMed Journal: Can J Nurs Res ISSN: 0844-5621