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- W1948022012 abstract "Hypotheses regarding how an independent variable affects a dependent variable via a mediating variable are widespread in both basic and applied psychology. This chapter focuses on statistical and design methods to investigate mediation relations rather than the substantive importance of mediation that is described elsewhere (MacKinnon, 2008). The chapter starts with detailed information on the single mediator model including covariance between estimates, measures of effect size, hypothesis testing, confidence limit estimation, and Bayesian methods. Causal inference approaches for mediation are described. Comprehensive mediation models are then discussed including models that accommodate both moderator and mediator variables, multiple mediators, multilevel models, and models that incorporate longitudinal relations among variables. We acknowledge that the identification of mediating variables can be a challenging process requiring a variety of information in addition to statistical analysis such as replication and experimental studies. Although the identification of mediating variables is a challenging task, many new statistical and methodological tools have been developed to help researchers.Keywords:data analysis;mediating variables;mediation analysis;statistics" @default.
- W1948022012 created "2016-06-24" @default.
- W1948022012 creator A5039216935 @default.
- W1948022012 creator A5052386555 @default.
- W1948022012 creator A5082531504 @default.
- W1948022012 date "2012-01-01" @default.
- W1948022012 modified "2023-10-13" @default.
- W1948022012 title "Statistical mediation analysis." @default.
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