Hi,
just recently I started my research on MLM, but now I'm little bit
confused... I tried to build a model, but now I'm not quite sure what's the
right thing I'm trying to do. The point is that I have a dataset with
counts and time of users activity. For example, it looks something like
this:
userID, group, department, organizationalUnit, activityCount, activityTime,
totalPoints
112,     g1,      d1,              o1                        232
    45,4              45
122,     g3,      d2,              o1                        323
    25,6              25
892,     g1,      d1,              o1                        98
    56,3              99
313,     g2,      d1,              o2                        332
    41,5              67
763,     g3,      d2,              o2                        555
    89.7              23

maybe the example itself it's not that important at this point, but I could
provide more data if that is needed. However, the original idea was to use
activitycount, totalpoints, organizationalUnit and department as a fixed
variables, as well as interactions between organizationalUnits vs. count
and time and, department vs. count and time. Random variables are usedId
and group\department. The problem occurs when I add department as a fixed
and/or random part, because of the following error:
Error in lme4::lFormula(formula = totalPoints~ activityCount  +
activityTime  + ...: rank of X = 38 < ncol(X) = 39.

I decided to remove group\department as a random effect, but that might not
be good, because I need group nested under department. I also tried to add
another random variable group\organizationalUnit | userID, which (I hope)
means that user varies across groups which are nested under the
organizational units. And I'm not sure about that part. In lmer (lmerTest)
documentation, I found several examples, which translated to this one could
be written like this:
group:organizationalUnit | userID
group\organizationalUnit | userID
group+organizationalUnit | userID

could someone please explain how those models are different, and what they
mean? I tried to run all of them but I run out of memory. I know that 8GB
of RAM is not too much, but it was enough for most of my tests. Should I
look for more RAM or should I correct my model? :)

thanks,
Srecko

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