Hi, I am new to the R programme. I wonder if you can help me with Variance Component analysis. In my data, I have 4 variables: managers’ performance (outcome), managers, exercise (interpersonal, decision-making...), and assessment methods (only two: Method A versus Method B). Each manager completes ALL exercises, and each time the exercise is assessed in both Method A and Method B. I want to examine how much of the variance of the outcome can be contributed to managers, exercise, method, and all their interactions (all 2-way and 3-way). 
 
I do not believe that managers, exercise, and assessment methods are CROSSED with each other.
 
Assume that managers, exercise, and assessment methods are all regarded as random factors, I do not know how to specify this model in R. Can someone please help me with this? I know how to set it up when the random effects do NOT interact with each other:
 
Model1 <- lmer (performance ~ (1|managers) + (1|exercise) + (1|method), data = mtmm)
 
However, when it involves interactions among the random effects, then I have no idea how to do it. In addition, I want to assume no correlation/covariance among the three random effects (i.e., variance component structure).
 
Only performance is a continuous variable. 
 
Thanks so much!
Chester
PhD Candidate
Dept of Psychology
Univ of Western Ontario


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