Dear All, I am trying to fit a simple linear mixed model (see below this paragraph) arising from a crossed factorial design with 2 factors and ubalanced number of replicates (from two to five) in each cell, but I keep getting an error message (see bottom of message). The model is:
yijk = intercept + ai + bj + abij + ejik, where: "intercept" is fixed, and the crosss factors, ai, i = 1,..,10, and bj, j= 1,..,10, are random. I am interested in estimating the variance components of these factors AND their interaction. I have tried: fm1 <- lmer(formula = V1~1 + (1|V2) + (1|V3) + (1|V4), data = 'datos') using two types of data layout for "datos": 1) using a matrix with 3 columns: y intercept ai's bj's abij's y111 1 1 1 1 (1x1) y112 1 1 1 " y121 1 1 2 2 (1x2) y122 1 1 2 " y123 1 1 2 " y131 1 1 3 3 (1x3) . . . . . . . . . . 2) using the design matrix from Y = XBeta +Zb. That is, using the same first two columns as above, but substituting 1020 columns (10 for ai's, 10 for bj's and 100 for abij's) for the last three columns. I get the message: "Error in eval(predvars, data, env) : invalid envir argument" Is my data layout mispecified? Do I need to input initial values for the random components in order to get the REML estimates? I lmer valid for unbalanced designs? Any help would be greatly appreciated. Rafael Diaz California State University Sacramento Math and Stats ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
