1. I'm attempting to test for Random Effects. I've grouped the data on subject (grid) but want to use lme to build the model without subject as a RE then add it and do anova between the 2 models. This is the result I get and it appears it's adding Random Effects.
tmp.dat4 <- groupedData(Trials ~ 1 | grid, data = tmp.dat4) mod2a <- lme(Trials ~ factor(group_id) + reversal, data = tmp.dat4, na.action = na.omit, method = "REML") > summary(mod2a) Linear mixed-effects model fit by REML Data: tmp.dat4 AIC BIC logLik 4544.054 4587.718 -2262.027 Random effects: Formula: ~factor(group_id) + reversal | grid Structure: General positive-definite StdDev Corr (Intercept) 10.505303 (Intr) fc(_)2 factor(group_id)2 9.830679 -0.778 reversal2 7.106839 -0.275 0.023 Residual 9.995963 Fixed effects: Trials ~ factor(group_id) + reversal Value Std.Error DF t-value p-value (Intercept) 23.275874 1.876185 510 12.405960 0e+00 factor(group_id)2 -7.639842 2.151004 72 -3.551757 7e-04 reversal2 7.681495 1.206858 510 6.364869 0e+00 Correlation: (Intr) fc(_)2 factor(group_id)2 -0.785 reversal2 -0.308 -0.015 Standardized Within-Group Residuals: Min Q1 Med Q3 Max -2.6884393 -0.5059063 -0.1892908 0.4944976 2.8477377 Number of Observations: 585 Number of Groups: 74 2. Secondly is this the correct way to add covariates (such as age). mod2i <- lme(Trials ~ factor(group_id)*factor(reversal) * age, data = tmp.dat4, random = ~ 1 | grid, na.action = na.omit, method = "ML") -- View this message in context: http://r.789695.n4.nabble.com/lme-Random-Effects-and-Covariates-tp3049181p3049181.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.