Third-variable effect refers to the effect transmitted by third-variables that intervene in the relationship between an exposure and a response variable. Differentiating between the indirect effect of individual factors from multiple third-variables is a constant problem for modern researchers.Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS introduces general definitions of third-variable effects that are adaptable to all different types of response (categorical or continuous), exposure, or third-variables. Using this method, multiple third- variables of different types can be considered simultaneously, and the indirect effect carried by individual third-variables can be separated from the total effect. Readers of all disciplines familiar with introductory statistics will find this a valuable resource for analysis.Key Features: Parametric and nonparametric method in third variable analysis Multivariate and Multiple third-variable effect analysis Multilevel mediation/confounding analysis Third-variable effect analysis with high-dimensional data Moderation/Interaction effect analysis within the third-variable analysis R packages and SAS macros to implement methods proposed in the book
Bin Li & Qingzhao Yu
Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS [EPUB ebook]
Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS [EPUB ebook]
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ภาษา อังกฤษ ● รูป EPUB ● หน้า 294 ● ISBN 9781000549485 ● สำนักพิมพ์ CRC Press ● การตีพิมพ์ 2022 ● ที่สามารถดาวน์โหลดได้ 3 ครั้ง ● เงินตรา EUR ● ID 8286960 ● ป้องกันการคัดลอก Adobe DRM
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