2016
DOI: 10.3102/1076998616636855
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Estimation of Indirect Effects in the Presence of Unmeasured Confounding for the Mediator–Outcome Relationship in a Multilevel 2-1-1 Mediation Model

Abstract: To assess the direct and indirect effect of an intervention, multilevel 2-1-1 studies with intervention randomized at the upper (class) level and mediator and outcome measured at the lower (student) level are frequently used in educational research. In such studies, the mediation process may flow through the student-level mediator (the within indirect effect) or a class-aggregated mediator (the contextual indirect effect). In this article, we cast mediation analysis within the counterfactual framework and clar… Show more

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Cited by 12 publications
(12 citation statements)
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“…It may be that unmeasured confounding variables are responsible for this unexpected finding. Indeed, between-dyads effects are more sensitive to potential confounders than within-dyads effects, and as such, the within-dyads effects may be interpreted with more certainty (see Talloen et al, 2016). Furthermore, our post hoc interpretations of between-dyads effects in terms of stable (or persistent) response styles and within-effects in terms of daily variation (or flexibility) in responding in parents are preliminary.…”
Section: Discussionmentioning
confidence: 99%
“…It may be that unmeasured confounding variables are responsible for this unexpected finding. Indeed, between-dyads effects are more sensitive to potential confounders than within-dyads effects, and as such, the within-dyads effects may be interpreted with more certainty (see Talloen et al, 2016). Furthermore, our post hoc interpretations of between-dyads effects in terms of stable (or persistent) response styles and within-effects in terms of daily variation (or flexibility) in responding in parents are preliminary.…”
Section: Discussionmentioning
confidence: 99%
“…We utilize a cross-level mediation approach as described by Pituch and Stapleton (2011; 2012; also see Krull & MacKinnon, 2001; Talloen et al, 2016; VanderWeele, 2010), where unlike the cluster-level only mediation approach (see Preacher et al, 2010; Zhang et al, 2009) a mediation process can flow through an individual-level mediator, if it is theoretically plausible that the individual-level outcome could be influenced by an individual-level mediator that reflects absolute scale value, not relative standing in a group. Our study satisfies these conditions as it is safe to assume that an employee’s personal LMX quality impacts employee cynicism and dedication, and further that it is the absolute level of LMX rather than relative position in the work-unit that is important.…”
Section: Methodsmentioning
confidence: 99%
“…Extension of the no-confounder assumption to a multilevel single mediator model has been discussed in the literature (Bind et al, 2016; Talloen et al, 2016; Tofighi & Kelley, 2016) We discuss extension of the no omitted confounder assumption to the LGCMM in Figure 1. Given that the hypothesized LGCMM has a randomized intervention ( X ), the no omitted confounder assumption is satisfied if the following two assumptions hold.…”
Section: Causal Assumptions In Latent Growth Curve Mediation Modelingmentioning
confidence: 99%
“…Using multilevel structural equation modeling (SEM) framework, Tofighi and Kelly (2016) proposed a post-hoc method to compute the omitted confounder effect on the point estimate of the indirect effect but did not offer a method to compute standard errors and CIs for adjusted indirect effects. Using the potential outcomes framework (Rubin, 1974, 1978), Talloen et al(2016) used fixed effect techniques (Allison, 2005) to remove the confounding bias at the Between level and thus relax the assumption of no omitted confounder at the Between level. The fixed effect technique cannot be applied to LGCMM in our study because the fixed-effect technique removes all the Between variability (McNeish & Kelley, 2018), which is the focus of our study.…”
mentioning
confidence: 99%