options(
contrasts = c(unordered = "contr.SAS", ordered = "contr.poly"))
data(Mississippi)
formula( Mississippi )
#plot( Mississippi )
fm1Miss <- lme( y ~ 1, data = Mississippi, random = ~ 1 | influent )
summary( fm1Miss ) # compare with output 4.1, p. 142
fm1MLMiss <- update( fm1Miss, method = "ML" )
summary( fm1MLMiss ) # compare with output 4.2, p. 143
random.effects( fm1MLMiss ) # BLUP's of random effects on p. 144
random.effects( fm1MLMiss , aug = TRUE ) # including covariates
random.effects( fm1Miss ) # BLUP's of random effects on p. 142
intervals( fm1Miss ) # interval estimates of variance components
VarCorr( fm1Miss ) # compare to output 4.7, p. 148
fm2Miss <- lme( y ~ Type, data = Mississippi, random = ~ 1 | influent,
method = "REML" )
summary( fm2Miss ) # compare to output 4.8 and 4.9, pp. 150-152
anova( fm2Miss )Run the code above in your browser using DataLab