[Mediation-information] Appropriate use of package "mediation"

dustin tingley dtingley at gov.harvard.edu
Thu Sep 15 04:27:16 CEST 2011

Hi Tormod-

To follow up, we do allow you to set two values of the treatment other than
0 or 1. Make sure you're using the latest version of the package (3.1), in R
2.13. As Kosuke mentions, it won't matter when everything is linear, but
when things are non-linear, then the ACME from 0 to 1 might different from a
3 to 4 change. This is typical of any time you use probit/logit etc. due to
the nature of the response function in those models.  Also, the sensitivity
analysis, is only worked out for the t=0 and t=1 case. Note that things like
MPlus won't calculate sensitivity analyses...Keep in mind the strong
assumptions you are making when conducting mediation analysis. For us, that
means running a sensitivity analysis if possible, or thinking about
alternative research designs.


Dustin Tingley
Government Department
Harvard University

On Wed, Sep 14, 2011 at 10:19 PM, Kosuke Imai <kimai at princeton.edu> wrote:

> Hi Tormod,
>  I'm ccing the listserv we have so that my collaborators and others can
> give additional insights.  The mediation software doesn't have the
> functionality to fully accomodate the continuous treatment.  However, when
> the software will calculate the average causal mediation effect of changing
> the treatment from 0 to 1.  If you use a linear model for both mediator and
> outcome, then this should be sufficient because the ACME would not change
> regardless of the base value you choose for the treatment.  If you have a
> nonlinear model, however, the ACME you get is still valid but only for the
> scenario where you change the treatment value from 0 to 1.  If you are
> thinking about different scenario (e.g., changing the treatment from 3 to
> 4), then you will get a different answer.
> Best,
> Kosuke
> Department of Politics
> Princeton University
> http://imai.princeton.edu
> On Sep 14, 2011, at 8:24 AM, Tormod Bøe wrote:
> > Dear Associate Professor Imai,
> >
> > I am currently doing a PhD at the University of Bergen. We have conducted
> a large-scale population based study of childhood mental health.
> >
> > I am in the process of writing at paper where we investigate to which
> extent sleep problems mediate the association between parental socioeconomic
> status and children's mental health problems.
> >
> > We have two sleep measures (one rated on a three point scale, and two
> that are binary[0=adequate sleep time, 1=long/short sleep time]), parental
> SES is continuous (years of education and family income rated on five point
> scales) and outcome is continuous (range 0-30).
> >
> > I have made some attempts at running mediation analyses using your R
> package mediation. I have made one model m where I regress family SES on
> sleep problems, and model y where I regress family SES and sleep problems on
> mental health problems outcome. I use sleep problems as "mediator" and have
> used SES variables (e.g. family economy) as treatment variables. However, is
> this an appropriate use of your package?
> >
> > I am especially concerned with regards to the use of a continuous
> "treatment" variable. The models run without any errors, and the pattern of
> results (with regards to significant interactions) resemble those I obtain
> when running path analyses in Mplus.
> >
> > If you could please provide some advice in this manner it would be
> greatly appreciated.
> >
> > Yours sincerely,
> > Tormod Bøe
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