<div dir="ltr">Prop Mediated is a ratio of two estimates, which are known to have a very high variance especially when the average treatment effect is not precisely estimated. I would focus on the point estimate of this quantity rather than its CI. The most important thing is the ACME which have a much more stable CI.</div><div class="gmail_extra"><br clear="all"><div><div class="gmail_signature"><div dir="ltr"><div>Kosuke Imai</div><div>Department of Politics<br></div><div>Princeton University</div><div><a href="http://imai.princeton.edu" target="_blank">http://imai.princeton.edu</a></div></div></div></div>
<br><div class="gmail_quote">On Tue, Jun 9, 2015 at 10:34 PM, Daniel Newman <span dir="ltr"><<a href="mailto:dan.newman86@gmail.com" target="_blank">dan.newman86@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr">Dear mediation gourp,<div><br></div><div>Firstly, thank you to Profs. Tingley, Yamamoto, Hirose, Keele, Imai, et al. for building this R package. I have just started using it. </div><div><br></div><div>I am a little confused about the difference between "Prop. Mediated (average)" and "ACME (average)". Could anybody help explain this to me? </div><div><br></div><div>For example, in the mediate summary below, the 95% CIs show that my "Prop. Mediated (average)" is significantly greater than zero, but the ACME (average) is not significantly greater than zero.</div><div><br></div><div><div>Causal Mediation Analysis </div><div><br></div><div>Quasi-Bayesian Confidence Intervals</div><div><br></div><div>Mediator Groups: AllConds </div><div><br></div><div>Outcome Groups: AllConds </div><div><br></div><div>Output Based on Overall Averages Across Groups </div><div><br></div><div> Estimate 95% CI Lower 95% CI Upper p-value</div><div>ACME (control) -0.0684 -0.1537 0.0103 0.1</div><div>ACME (treated) -0.2053 -0.4612 0.0308 0.1</div><div>ADE (control) -3.0298 -6.8686 0.4929 0.1</div><div>ADE (treated) -3.1667 -7.1734 0.5134 0.1</div><div>Total Effect -3.2351 -7.3259 0.5237 0.1</div><div>Prop. Mediated (control) 0.0213 0.0139 0.0291 0.0</div><div>Prop. Mediated (treated) 0.0640 0.0417 0.0873 0.0</div><div><b>ACME (average) </b> -0.1369 -0.3075 0.0205 0.1</div><div>ADE (average) -3.0983 -7.0210 0.5032 0.1</div><div><b>Prop. Mediated (average)</b> 0.0427 0.0278 0.0582 0.0</div></div><div><br></div><div><br></div><div>This output above was generated from the code below - a mediation model to test whether the continuous mediator ("PrePupilDiameter ") mediates the relationship between the categorical treatment ("Light") and the continuous dependent variable ("RT") :</div><div><br></div><div>med.fit<-lmer(PrePupilDiameter ~ Light + (1 | AllConds), data = data_LeftTargets, na.action = na.exclude)</div><div>out.fit<-lmer(RT ~ PrePupilDiameter + Light + PrePupilDiameter * Light + (1 | AllConds), data = data_LeftTargets, na.action = na.exclude)</div><div>med.out <- mediate(med.fit, out.fit, treat = "Light", mediator = "PrePupilDiameter", control.value = 1, treat.value = 3, sims = 100, outcome="RT")</div><div>summary(med.out) <br clear="all"><div><br></div><div>Any help explaining to me the difference between "Prop. Mediated (average)" and "ACME (average)" would be much appreciated </div><div><br></div><div>Cheers</div><div>Dan</div><div><br></div>
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