Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS (eBook)

Bin Li, Qingzhao Yu (Autoren)

eBook Download: PDF

2022
294 Seiten
CRC Press (Verlag)
978-1-000-54941-6 (ISBN)

Infos

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

Produkt-Details

• Erscheint lt. Verlag: 14.3.2022
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• ISBN-10: 1-000-54941-0 / 1000549410
• ISBN-13: 978-1-000-54941-6 / 9781000549416