
Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS
Format: Paperback
ISBN13: 9781032220086
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Overview
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
| ISBN-13 | 9781032220086 |
|---|---|
| ISBN-10 | 1032220082 |
| Weight | 0.91 Pounds |
| Dimensions | 6.14 x 0.67 x 9.21 In |
| List Price | $61.99 |
| Edition | 1st Edition |
| Format | Paperback |
|---|---|
| Language | English |
| Pages | 294 pages |
| Publisher | Chapman and Hall/CRC |
| Published On | 2024-05-27 |
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