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<P><FONT SIZE=2>Thank you, Mashhood, for your answer.<BR>
<BR>
If I understand correctly, you recommend I run two models:<BR>
<BR>
infant deprivation --> education level --> aging well (plus age, gender, region)<BR>
<BR>
education level --> economic position --> aging well (plus age, gender, region)<BR>
<BR>
<BR>
Because the effects of infant deprivation are considered in the first model, there is no need to include it as a confounder in the second model.<BR>
<BR>
Is that correct?<BR>
<BR>
Angel Rodriguez-Laso<BR>
<BR>
<BR>
-----Mensaje original-----<BR>
De: mediation-information-bounces@lists.r-forge.r-project.org en nombre de Mashhood Sheikh<BR>
Enviado el: mar 26/08/2014 15:01<BR>
Para: mediation-information@lists.r-forge.r-project.org<BR>
Asunto: Re: [Mediation-information] Mediation-information Digest, Vol 25,Issue 2<BR>
<BR>
In order to assess if the effect of education on ageing well is partly or completely mediated by economic position, you can run this model (adjusted for all potential confounders):<BR>
<BR>
education level --> economic position --> aging well <BR>
<BR>
---<BR>
Mashhood Ahmed Sheikh<BR>
Research Fellow,<BR>
Department of Community Medicine, <BR>
Faculty of Health,<BR>
University of Tromsų,<BR>
Norway<BR>
<BR>
<BR>
<BR>
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> 1. Causally dependent mediators (Angel Rodriguez)<BR>
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> Message: 1<BR>
> Date: Tue, 26 Aug 2014 00:14:31 +0200<BR>
> From: "Angel Rodriguez" <angel.rodriguez@matiainstituto.net><BR>
> To: <mediation-information@lists.r-forge.r-project.org><BR>
> Subject: [Mediation-information] Causally dependent mediators<BR>
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> Dear subscribers,<BR>
><BR>
><BR>
> I'm interested in using mediation for the following conceptual model applied to survey data:<BR>
><BR>
> infant deprivation (binary) --> education level (ordered categorical) --> economic position (continous) --> aging well (dichotomous outcome)<BR>
><BR>
> I assume that, apart from the mediation effects, each link has direct effects on the outcome.<BR>
><BR>
> I've read in "Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies" (Imai et al 2011), that studying education as the main mediator wouldn't be a problem, because the sequential ignorability assumption would be met due to the fact that the second mediator is downstream (figure 6d of that paper). That would be my first model.<BR>
><BR>
> What should I do to know if the effect of education is partly or completely mediated by economic position? I understand I cannot use economic position as a main mediator in the model deprivation --> economic position --> aging well, because there would be an upstream mediator (education), which violates the sequential ignorability. I should use multimed then (my second model):<BR>
><BR>
><BR>
> R> Xnames <- c("age","gender", "region")<BR>
> R> set.seed(2014)<BR>
> R> m.med <- multimed(outcome = "agingwell", med.main = "economic", med.alt = "education",<BR>
> + treat = "deprivation", covariates = Xnames,<BR>
> + data = framing, sims = 1000)<BR>
> R> summary(m.med)<BR>
><BR>
><BR>
> If I get a large mediating effect of "education" in my first model and a negligible effect of "economic" in the second, could I conclude that all the mediating effect of "education" on the relationship between "deprivation" and aging well is driven by "economic"?<BR>
><BR>
> I suppose I cannot analyse multilevel data with multimed.<BR>
><BR>
><BR>
><BR>
> Thank you very much.<BR>
><BR>
> Angel Rodriguez-Laso<BR>
> Research Project Manager<BR>
> Matia Instituto Gerontol?gico<BR>
><BR>
><BR>
><BR>
><BR>
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