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I'm trying to look for significant effects on "similarity" (of "isinpair" and controlling for time effects) using repeated measures with an in group sample. The intervention "isinpair" occurs after a short period of time (time intervals aren't equivalent, but there are many occuring with in a relative short time).

The question seems a variation of R's lmer cheat-sheet

Unfortunately, I am quite hazy about the syntax (and underlying statistical differences) of lme vs. lmer. I've seen both recommended for similar tasks.

  1. Are these two examples accomplishing what I intend? How equivalent / different are they? Which is better illustrating what I'm hoping to examine?

    lmer(similarity ~ 1 +time*isinpair +(time*isinpair|user1), data=nozeros) 
    lme(similarity ~ isinpair*time, random=list(user1=pdBlocked(list(~1, 
                       pdIdent(~isinpair-1), pdIdent(~time-1)))), data=nozeros)
  2. How does this compare to:

    aov(simscore ~ isinpair * time + Error(user1), data = nozerosdemo))

marked as duplicate by gung - Reinstate Monica r Aug 10 '18 at 0:36

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