Extract the modes of the random effect — ranef.fastlmm • fastglmm

Extract the conditional modes of the random effect from the model fit

Usage

# S3 method for class 'fastlmm'
ranef(object, ...)

Arguments

object: fitted model of class fastlmm
...: other args, not used

Examples

library(MASS)

# GLMM via PQL
fit <- fastglmm(y ~ trt + I(week > 2) + (1 | ID),
   family = binomial(), data = bacteria)

ranef(fit)
#> $ID
#>            [,1]
#> X01  0.63621469
#> X02 -0.40298133
#> X03  1.39761822
#> X04  0.78319180
#> X05  0.78319180
#> X06  1.19078417
#> X07 -1.66773921
#> X08 -0.61233282
#> X09  0.78319180
#> X10  0.63098249
#> X11  0.78319180
#> X12 -0.55440704
#> X13  0.78319180
#> X14 -1.31451616
#> X15  1.39761822
#> X16 -0.08980838
#> X17 -0.61233282
#> X18 -1.28377835
#> X19 -1.50898465
#> X20  0.95128437
#> X21  0.78319180
#> Y01  0.78319180
#> Y02 -2.25565387
#> Y03 -0.93343929
#> Y04 -1.86931374
#> Y05 -2.49580840
#> Y06  0.63621469
#> Y07 -0.55440704
#> Y08 -0.16217779
#> Y09  0.75454840
#> Y10  0.26175241
#> Y11  0.78319180
#> Y12  0.63098249
#> Y13 -1.86931374
#> Y14  0.44662392
#> Z01  0.90538719
#> Z02  0.78319180
#> Z03  1.13556043
#> Z05 -1.50898465
#> Z06 -1.06787838
#> Z07 -0.55440704
#> Z09  0.95128437
#> Z10  0.78319180
#> Z11  1.39761822
#> Z14 -0.08980838
#> Z15  1.13430030
#> Z19  1.13556043
#> Z20 -1.00111946
#> Z24 -0.93343929
#> Z26 -0.08980838
#>