Advances in mediation analysis: a survey and synthesis of new developments.

By Kristopher J Preacher. Annual Review of Psychology, 2015

747 citations recorded by the source corpus.

Subfields: Clinical Psychology, Experimental and Cognitive Psychology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/548a8691bb047c618773b98663b945a20538e0be

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In Clinical Psychology

In Experimental and Cognitive Psychology

In Statistics and Probability

Citations in the corpus

Regression-based statistical mediation and moderation analysis in clinical research: Observations, recommendations, and implementation. (2017, background): “…argue that one cannot conduct a mediation analysis with merely correlational data, that moderators must be independent of presumed causes of effects, and the lis of requirements goes on and on (see e.g., Emsley, Dunn, & White, 2010; Preacher, 2015, for a discussion of many of these assumptions).”
Psychosocial safety climate as a moderator of the moderators: Contextualizing JDR models and emotional demands effects (2018, background): “While the ‘correct time lag’ (Dormann & Griffin, 2015) is often debatable (Preacher, 2015), the effects are influenced by various factors including the stability of variables (Dormann & Griffin, 2015) and the types of strain (Ford et al., 2014).”
Conditional Process Analysis: Concepts, Computation, and Advances in the Modeling of the Contingencies of Mechanisms (2020, background): “But the dangers of artificially categorizing continuous variables prior to analysis is well documented (e.g., Rucker, McShane, & Preacher, 2015), and its pitfalls likely generalize to multiple group SEM.”
Partisan News and Political Participation: Exploring Mediated Relationships (2016, methodology): “The total effect of the independent variable on the dependent variable is the sum of the direct effect and the specific indirect effects (see Preacher, 2015).”
The influence of flow experience in the augmented reality context on psychological ownership (2021, positive): “.765 Chi-square ¼ 585.074, DF ¼ 161, P¼ 0.000, CMIN/DF ¼ 3.568, RMR ¼ 0.048, CFI ¼ 0.934, IFI ¼ 0.935, RMSEA ¼ 0.069. estimate the mediating effect (Preacher 2015).”
Partial, conditional, and moderated moderated mediation: Quantification, inference, and interpretation (2018, background): “…all very similar though differing in emphasis, to answering the question as to whether mediation is moderated (e.g., Edwards & Lambert, 2007; Fairchild & MacKinnon, 2009; Hayes, 2015; Hayes & Preacher, 2013; Muller, Judd, & Yzerbyt, 2005; Preacher, Rucker, & Hayes, 2007; Wang & Preacher, 2015).”
Messages about brilliance undermine women's interest in educational and professional opportunities (2018, neutral): “First, the conclusions drawn from our mediation analyses are necessarily limited by their correlational nature (e.g., Preacher, 2015).”
Determining Power and Sample Size for Simple and Complex Mediation Models (2017, background): “Several authors have provided detailed reviews of mediation analysis (Gunzler, Chen, Wu, & Zhang, 2013; Hayes, 2009, 2013; MacKinnon, 2008; Preacher, 2015; Rucker, Preacher, Tormala, & Petty, 2011), but discussions on power analysis and sample size calculations for these models are relatively sparse”