Hi, I have been using the mediation package in R to test for mediation in multilevel data. My data is as follows: X: continuous, M: binary, and Y: binary (Y:outcome, M: mediator) I'm testing a 1-1-1 mediation.
I get different results when I use random slopes in the equations and when I don't. My code is as follows: > med.fit <- glmer(M ~ X + (1+X | Subject), family = binomial(link = "logit"), data = data1, control=glmerControl(optimizer="bobyqa", check.conv.sing="warning")) > out.fit <- glmer(Y ~ M+ X + (1 + M + X | Subject), family = binomial(link = "logit"), data = data1, control=glmerControl(optimizer="bobyqa", check.conv.sing="warning")) > med.out <- mediate(med.fit, out.fit, treat = "X", mediator = "M", sims = 1000) > summary(med.out) With one part of my data I get a singular fit error for the out.fit command. When I only use (1|Subject) instead of (1+M+X|Subject), then I don't get this error, but I get totatlly different results in terms of mediation. Could you please help me? Should I use random slopes or not? Is the singular fit error a serious error? (Correlations within data are not very high, around .10-.15). Thank you. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.