<div dir="ltr">All the results are presented on the same scale as the outcome variable. So, if you are running the count model (e.g., poisson), you can interpret the ACME as the expected count.<div><br></div><div>Kosuke</div></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 Wed, May 6, 2015 at 11:15 PM, Elizabeth Pasipanodya <span dir="ltr"><<a href="mailto:epasipanodya@psych.udel.edu" target="_blank">epasipanodya@psych.udel.edu</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div lang="EN-US" link="blue" vlink="purple"><div><p class="MsoNormal"><span style="color:#1f497d">Hello All,<u></u><u></u></span></p><p class="MsoNormal"><span style="color:#1f497d"><u></u> <u></u></span></p><p class="MsoNormal"><span style="color:#1f497d">I am a doctoral student working on data from a project focusing on couples coping with breast cancer. I have a mediation model with two simultaneous predictors, X1 (a positive relationship event) and X2 (a relationship conflict), a mediator, M (a measure of intimacy), and an outcome Y (a measure of anxiety). X1 and X2 are both binary while M is continuous. Additionally, Y follows a count distribution. These variables are repeatedly measured for each individual across a number of days and, thus, I used the R packages lme4 and mediation to conduct my analyses.<u></u><u></u></span></p><p class="MsoNormal"><span style="color:#1f497d"><u></u> <u></u></span></p><p class="MsoNormal"><span style="color:#1f497d">I would like to double-check the meaning of the ACME. My understanding is that it represents the expected difference in the potential outcome when the mediator takes the value that it would have under the treatment condition compared to the control condition, while the treatment condition is held constant. Since I have a count outcome, should I report and interpret my ACME in the same units as my count outcome, as one would a rate ratio? That is, the ACME shall represent, in the logs of expected counts, the estimated average change in Y among the treatment group (those with a relationship event) as a result of M (intimacy) rather than directly from X1 (positive relationship event) and X2 (negative relationship event)? <u></u><u></u></span></p><p class="MsoNormal"><span style="color:#1f497d"><u></u> <u></u></span></p><p class="MsoNormal"><span style="color:#1f497d">For instance, based on the mediation output below, could I say something like the following --- on a day in which participants reported experiencing at least one negative relationship event, their estimated average change in anxiety due to changes in intimacy was 1.08 times (e^0.07485) that of those without a relationship conflict, controlling for the occurrence of positive relationship events?<u></u><u></u></span></p><p class="MsoNormal"><u></u> <u></u></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:blue;background:#e1e2e5">> med2 <- mediate(apath, bpath, treat = "X2", mediator = "M", sims=5000, control.value = -0.5, treat.value = 0.5, dropobs=TRUE, method = "boot", boot.type = "bca")<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:blue;background:#e1e2e5">> summary(med2)<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Causal Mediation Analysis <u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Quasi-Bayesian Confidence Intervals<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Mediator Groups: ID <u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Outcome Groups: ID <u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Output Based on Overall Averages Across Groups <u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"> Estimate 95% CI Lower 95% CI Upper p-value<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">ACME (control) 0.07890 0.02639 0.15107 0.00<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">ACME (treated) 0.07080 0.02354 0.13856 0.00<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">ADE (control) -0.06645 -0.32283 0.17712 0.50<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">ADE (treated) -0.07455 -0.35353 0.19218 0.50<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Total Effect 0.00435 -0.25810 0.26892 0.97<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Prop. Mediated (control) 0.16404 -11.47515 12.32893 0.97<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Prop. Mediated (treated) 0.20262 -9.82740 10.87888 0.97<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">ACME (average) 0.07485 0.02583 0.14364 0.00<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">ADE (average) -0.07050 -0.33728 0.18478 0.50<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Prop. Mediated (average) 0.18333 -10.80037 11.56373 0.97<u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Sample Size Used: 602 <u></u><u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5"><u></u> <u></u></span></p><p class="MsoNormal" style="word-break:break-all"><span style="font-size:10.0pt;font-family:"Lucida Console";color:black;background:#e1e2e5">Simulations: 5000 <u></u><u></u></span></p><p class="MsoNormal"><u></u> <u></u></p><p class="MsoNormal">Best,<span class="HOEnZb"><font color="#888888"><u></u><u></u></font></span></p><span class="HOEnZb"><font color="#888888"><p class="MsoNormal"><u></u> <u></u></p><p class="MsoNormal">Elizabeth Pasipanodya<u></u><u></u></p><p class="MsoNormal"><u></u> <u></u></p><p class="MsoNormal"><u></u> <u></u></p></font></span></div></div><br>_______________________________________________<br>
Mediation-information mailing list<br>
<a href="mailto:Mediation-information@lists.r-forge.r-project.org">Mediation-information@lists.r-forge.r-project.org</a><br>
<a href="https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/mediation-information" target="_blank">https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/mediation-information</a><br></blockquote></div><br></div>