VCA (version 1.5.1)

reScale: Re-Scale results of 'VCA' or 'VCAinference'

Description

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.

Usage

reScale(obj, VarVC = TRUE)

Value

(object) either of class 'VCA' or 'VCAinference', where results have been transformed back to the original scale of the response variable

Arguments

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!

Author

Andre Schuetzenmeister

See Also

Scale

Examples

if (FALSE) {
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")
}