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fabian-s / RLRsim

R package for fast & exact (restricted) likelihood ratio tests for mixed and additive models
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model.matrix warning about contrasts #10

Closed fabian-s closed 2 years ago

fabian-s commented 2 years ago 
### R code from vignette source 'Ch-LME.Rnw'

###################################################
### code chunk number 1: setup
###################################################
library("MVA")
set.seed(280875)

###################################################
### code chunk number 2: setup
###################################################
library("nlme")

###################################################
### code chunk number 6: ch:LME:timber:tab
###################################################
"timber" <-
matrix(c(0., 0., 0., 0., 0., 0., 0., 0., 2.3799999999999999, 2.6899999999999999, 2.8500000000000001, 2.46,
        2.9700000000000002, 3.96, 3.1699999999999999, 3.3599999999999999, 4.3399999999999999, 4.75,
        4.8899999999999997, 4.2800000000000002, 4.6799999999999997, 6.46, 5.3300000000000001, 5.4500000000000002,
        6.6399999999999997, 7.04, 6.6100000000000003, 5.8799999999999999, 6.6600000000000001, 8.1400000000000006,
        7.1399999999999997, 7.0800000000000001, 8.0500000000000007, 9.1999999999999993, 8.0899999999999999,
        7.4299999999999997, 8.1099999999999994, 9.3499999999999996, 8.2899999999999991, 8.3200000000000003,
        9.7799999999999994, 10.94, 9.7200000000000006, 8.3200000000000003, 9.6400000000000006, 10.720000000000001,
        9.8599999999999994, 9.9100000000000001, 10.970000000000001, 12.23, 11.029999999999999, 9.9199999999999999,
        11.06, 11.84, 11.07, 11.06, 12.050000000000001, 13.19, 12.140000000000001, 11.1, 12.25, 12.85,
        12.130000000000001, 12.210000000000001, 12.98, 14.08, 13.18, 12.23, 13.35, 13.83, 13.15, 13.16, 13.94,
        14.66, 14.119999999999999, 13.24, 14.539999999999999, 14.85, 14.09, 14.050000000000001, 14.74,
        15.369999999999999, 15.09, 14.19, 15.529999999999999, 15.789999999999999, 15.109999999999999,
        14.960000000000001, 16.129999999999999, 16.890000000000001, 16.68, 16.07, 17.379999999999999,
        17.390000000000001, 16.690000000000001, 16.239999999999998, 17.98, 17.780000000000001, 17.940000000000001,
        17.43, 18.760000000000002, 18.440000000000001, 17.690000000000001, 17.34, 19.52, 18.41, 18.219999999999999,
        18.359999999999999, 19.809999999999999, 19.460000000000001, 18.710000000000001, 18.23, 19.969999999999999,
        18.969999999999999, 19.399999999999999, 18.93, 20.620000000000001, 20.050000000000001, 19.539999999999999,
        18.870000000000001)
, nrow = 8, ncol = 15)

slippage <- c((0:10)/10, seq(from = 1.2, to = 1.8, by = 0.2))

colnames(timber) <- paste("s", slippage, sep = "")
timber <- as.data.frame(timber)
timber$specimen <- factor(paste("spec", 1:nrow(timber), sep = ""))

timber.dat <- reshape(timber, direction = "long", idvar = "specimen",
        varying = matrix(colnames(timber)[1:15], nr = 1),
        timevar = "slippage")
names(timber.dat)[3] <- "loads"
timber.dat$slippage <- slippage[timber.dat$slippage]
timber <- timber.dat

###################################################
### code chunk number 11: ch:LME:timber:lme
###################################################
timber.lme <- lme(loads ~ slippage, 
                  random = ~1 | specimen,
                  data = timber, method = "ML")

###################################################
### code chunk number 12: ch:LME:timber:LRT
###################################################
library("RLRsim")

exactRLRT(timber.lme)
#Using restricted likelihood evaluated at ML estimators.
#Refit with method="REML" for exact results.

#   simulated finite sample distribution of RLRT.

#   (p-value based on 10000 simulated values)

#data:  
#RLRT = 3.2183e-07, p-value = 0.4419

#Warning message:
#In model.matrix.default(~m$groups[[n.levels - i + 1]] - 1, contrasts.arg = c("contr.treatment",  :
#  non-list contrasts argument ignored