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

Third-variable effect refers to the intervening effect of a third-variable on the observed relationship between an exposure and an outcome. The third-variable effect analysis differentiates the effect from multiple third variables that explain the established exposure-outcome relationship. Depending on whether there is a causal relationship from the exposure to the third variable to the outcome, the third-variable effect can be categorized into two major groups: mediation effect where a causal relationship is assumed and confounding effect where there is no causal relationship. A causal relationship can be established through randomized experiments--

• | Author: Qingzhao Yu, Bin Li
• | Publisher: CRC Press LLC
• | Publication Date: May 27, 2024
• | Number of Pages: NA pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 1032220082
• | ISBN-13: 9781032220086