[R] converting proc mixed to lme for a random effects meta-analysis

From: Lucia Costanzo <lcostanz_at_uoguelph.ca>
Date: Tue, 19 Jun 2007 08:13:30 -0400

I would like to convert the following SAS code for a Random Effects meta-analysis model for use in R but, I am running into difficulties. The results are not similar, R should be reporting 0.017 for the between-study variance component, 0.478 for the estimated parameter and 0.130 for the standard error of the estimated parameter. I think it is the weighting causing problems. Would anyone have any suggestions or tips?

Thank you,

re.teo<-lme(y~1, data=genData2, random =~1, method="ML", weights=varFixed(~w))

data tacrine;

    input study y w;

    1 0.284 14.63
    2 0.224 17.02
    3 0.360  9.08
    4 0.785 33.03
    5 0.492  5.63


*Random Effects using log-odds for tacrine example table 4.29;
DATA remlma;

    SET tacrine;
    col = _n_;
    row = _n_;
    value = var;

*random effects for tacrine example;

PROC MIXED data = remlma method=reml order=data;

   CLASS study;
   MODEL y = / solution;
   RANDOM study / gdata = remlma;
   REPEATED diag;

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