Hello everyone, i'm new here but this is my absolute last resort..
For my master thesis i need to conduct a 111 within-person mediation analysis. I found the tutorial by Bolger & Lourenco and i succesfully managed to run the analysis.
Now my thesis supervisor wants me to do a full check of the model assumptions of this specific model (see below). I have searched far and wide across the internet yet was not able to find a single tutorial, post, etc. that helps explain how to check the model-assumptions of a stacked model like this.
Is there any good soul out there that might possibly know a link, article, has R-code themselves, anything(!) to check the model-assumptions?
I would be forever grateful!
model.lme <- lme(fixed= z ~ 0 + dm + dy +
dm:RSOScentered + dm:metingc +
dy: pstotafwijking + dy:RSOScentered + dy:metingc,
random= ~ 0 + dm:RSOScentered + dy: pstotafwijking + dy:RSOScentered|deelnemer,
weights= varIdent(form = ~ 1|dvnum),
data= datalong,
na.action=na.exclude,
control=lmeControl(opt="optim",maxIter=200,
msMaxIter=200, niterEM=50, msMaxEval = 400))
summary(model.lme)
For my master thesis i need to conduct a 111 within-person mediation analysis. I found the tutorial by Bolger & Lourenco and i succesfully managed to run the analysis.
Now my thesis supervisor wants me to do a full check of the model assumptions of this specific model (see below). I have searched far and wide across the internet yet was not able to find a single tutorial, post, etc. that helps explain how to check the model-assumptions of a stacked model like this.
Is there any good soul out there that might possibly know a link, article, has R-code themselves, anything(!) to check the model-assumptions?
I would be forever grateful!
model.lme <- lme(fixed= z ~ 0 + dm + dy +
dm:RSOScentered + dm:metingc +
dy: pstotafwijking + dy:RSOScentered + dy:metingc,
random= ~ 0 + dm:RSOScentered + dy: pstotafwijking + dy:RSOScentered|deelnemer,
weights= varIdent(form = ~ 1|dvnum),
data= datalong,
na.action=na.exclude,
control=lmeControl(opt="optim",maxIter=200,
msMaxIter=200, niterEM=50, msMaxEval = 400))
summary(model.lme)