Mediation Models for Longitudinal Data in Developmental Research

By J. Selig, Kristopher J Preacher. 2009

817 citations recorded by the source corpus.

Subfields: Clinical Psychology, Education, Social Psychology

View Paper: https://www.semanticscholar.org/paper/388816c2ad57f4e1935f9736dc74016bb1d922f0

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In Clinical Psychology

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Citations in the corpus

The Relationship Between Media Multitasking and Attention Problems in Adolescents: Results of Two Longitudinal Studies (2017, background): “Choosing several time lags may be particularly important if no prior research exists because it allows comparing of e ﬀ ects and provides recommendations for future studies (Selig & Preacher, 2009).”
Bias in Cross-Sectional Analyses of Longitudinal Mediation: Partial and Complete Mediation Under an Autoregressive Model (2011, background): “For example, much attention has been devoted to studying mediation at the level of the individual, as can be done in multilevel modeling and latent growth curve frameworks (eg, Bauer, Preacher, & Gil, 2006 ; Kenny et al, 2003 ; Raykov & Mels, 2007 ; Selig & Preacher, 2009 ).”
Personality change via work: a job demand–control model of Big-five personality changes (2016, background): “A research design with multiple time periods would be ideal to unpack the directional effects between work environment/experience changes and personality changes (Selig & Preacher, 2009).”
Fostering task and adaptive performance through employee well-being: The role of servant leadership (2020, methodology): “The utilized LCSM was the most suitable analytical approach as it captures within-person changes in a construct across two time points and enables us to examine relationships among such within-person changes (Henk & CastroSchilo, 2016; McArdle, 2009; Selig & Preacher, 2009).”
Two-condition within-participant statistical mediation analysis: A path-analytic framework. (2017, methodology): “Additional alternatives include latent difference score approaches to mediation, which are beyond the scope of this manuscript, but are aptly described in MacKinnon (2008) and Selig and Preacher (2009).”
Acceptance- and mindfulness-based interventions for the treatment of chronic pain: a meta-analytic review (2016, background): “It must be scheduled in such a way that one is most certain to catch unfolding of processes one is interested in (Selig & Preacher, 2009).”
Conceptual and methodological issues in studying school leadership effects as a reciprocal process (2011, neutral): “Since no one lag is sufficient to fully reveal the nature of a proposed causal relationship, the use of varying lags within or across studies should be considered (Selig & Preacher, 2009 ).”
Determining Power and Sample Size for Simple and Complex Mediation Models (2017, background): “Implementing models that are the most common in and relevant to social psychology research, such as dyadic mediation models (Ledermann, Macho, & Kenny, 2011), longitudinal mediation models (Selig & Preacher, 2009), or models combining mediation and moderation (Hayes, 2013), is our priority.”
Studying Changes in Life Circumstances and Personality: It's about Time (2014, background): “Furthermore, the mediating variables should be measured before the outcome variables to allow testing one of the defining features of causal chains, temporal precedence (for statistical approaches to testing longitudinal mediation, see Selig & Preacher, 2009).”
Longitudinal relations between perceived autonomy and social support from teachers and students' self-regulated learning and achievement (2016, background): “Many authors have addressed the importance of choosing the right time interval for the measurements in longitudinal studies (Cole & Maxwell, 2003; Collins & Graham, 2002; Selig & Preacher, 2009).”