Statistical Methods For Mediation, Confounding And Moderation Analysis Using R And Sas Av Qingzhao Yu, Bin (Louisiana State University La Usa) Li

<p>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.</p><p><b><i>Statistical Methods for Mediation, Confounding and Moderation Analysis Using R and SAS </i></b>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.</p><p>Key Features:</p><ul><li>Parametric and nonparametric method in third variable analysis</li><li>Multivar