R help - May 2017 - mixed Model: asreml-r versus nmle,lme4 or coxme

Hi,

Did somebody know why asreml does not provide the same REML loglikehood  as
coxme, lme4 or lmne.
Here is a simple example showing the differences:


#######################################################################
library(lme4)
library(coxme)
library(asreml)
library(nlme)

data(ergoStool, package="nlme") # use a data set from nlme

fit1 <- lmekin(effort ~ Type+(1|Subject),
data=ergoStool,method="REML")
fit1$loglik #-60.56539
fit2 <- lmer(effort ~ Type+(1|Subject), data=ergoStool,REML=TRUE)
logLik(fit2) #'log Lik.' -60.56539 (df=6)
fit3<-asreml(fixed=effort ~ Type,random=~Subject,data=ergoStool,
        na.method.X="omit",na.method.Y="omit")
fit3$loglik #-31.15936
fit4<-lme(effort ~ Type,random=~1|Subject, data =
ergoStool,method="REML")
fit4$logLik  #-60.56539

fit1 <- lmekin(effort ~ (1|Subject), data=ergoStool,method="REML")
fit1$loglik #-78.91898
fit2 <- lmer(effort ~ (1|Subject), data=ergoStool,REML=TRUE)
logLik(fit2) #'log Lik.' -78.91898 (df=3)
fit3<-asreml(fixed=effort ~ 1,random=~Subject,data=ergoStool,
        na.method.X="omit",na.method.Y="omit")
fit3$loglik #-46.75614
fit4<-lme(effort ~ 1,random=~1|Subject, data =
ergoStool,method="REML")
fit4$logLik #-78.91898


############################
If it was just a constant value between the two models (with or without the
fixed effect) it would not be important. But it is not.
I checked that the variance component estimators were equal.

Thanks



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