Re-Scale results of 'VCA' or 'VCAinference'
Function adjusts variance components (VC) and standard deviations (SD) and their respective confidence intervals of 'VCAinference' objects, and the 'VCAobj' sub-element. For 'VCA' objects the VC and SD values are adjusted as well as the fixed and random effects and the covariance-matrix of fixed effects.
reScale(obj, VarVC = TRUE)
obj |
(object) either of class 'VCA' or 'VCAinference' |
VarVC |
(logical) TRUE = variance-covariance matrix of the fitted model 'obj' will be computed and automatically re-scaled, FALSE = variance-covariance matrix will not be computed and re-scaled. This might cause wrong results in downstream analyses which require this matrix on the correct scale! Only use this option if computation time really matters! |
(object) either of class 'VCA' or 'VCAinference', where results have been transformed back to the original scale of the response variable
Andre Schuetzenmeister andre.schuetzenmeister@roche.com
## Not run:
data(dataEP05A2_3)
# reference values
fit0 <- anovaVCA(y~day/run, dataEP05A2_3, MME=TRUE)
inf0 <- VCAinference(fit0, VarVC=TRUE)
fit1 <- Scale("anovaVCA", y~day/run, dataEP05A2_3, MME=TRUE)
inf1 <- VCAinference(fit1, VarVC=TRUE)
inf1 <- reScale(inf1)
# compare to reference
print(inf0, what="VC")
print(inf1, what="VC")
print(inf0, what="SD")
print(inf1, what="SD")
print(inf0, what="CV")
print(inf1, what="CV")
# now use REML-based estimation
fit0 <- remlVCA(y~day/run, dataEP05A2_3)
inf0 <- VCAinference(fit0)
fit1 <- Scale("remlVCA", y~day/run, dataEP05A2_3, MME=TRUE)
inf1 <- VCAinference(fit1)
inf1 <- reScale(inf1)
# compare to reference
print(inf0, what="VC")
print(inf1, what="VC")
print(inf0, what="SD")
print(inf1, what="SD")
print(inf0, what="CV")
print(inf1, what="CV")
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.