I'm trying to use mixed-effects modelling to analyse some data. There are a number of variables that I need to specify within the model, two of which are between-participants (
x2) and two of which are repeated-measures (
z2). I'm interested in individual differences both generally and in relation to the repeated-measure variables.
From what I understand, according to Barr's (2012) 'Keep it maximal' paper, the
lmer syntax should be:
y ~ x1*x2*z1*z2+ (1+(z1*z2)|ID)
When I try to run this in
R, it fails, I think the error message is telling me that I've over-specified the model:
Error in checkZdims(reTrms$Ztlist, n = n, control, allow.n = FALSE) : number of observations (=289) <= number of random effects (=292) for term ((z1 * z2) | ID); the random-effects parameters and the residual variance (or scale parameter) are probably unidentifiable
Is there a way to maximally specify my model, or do I need to restrict my random effects term? If so, what would the new term be?