Model.Fit {CorrMixed}

Compare the fit of linear mixed-effects models

Description

This function compares the fit of Model 1 (random intercept) and 2 (random intercept and Gausssian serial correlation), and of Model 2 (random intercept and Gausssian serial correlation) and 3 (random intercept, slope and Gausssian serial correlation)

Usage

Model.Fit(Model.1, Model.2)

Arguments

Model.1

An object of class WS.Corr.Mixed, the first fitted model.

Model.2

Another object of class WS.Corr.Mixed, the second fitted model.

Author(s)

Wim Van der Elst, Geert Molenberghs, Ralf-Dieter Hilgers, & Nicole Heussen

References

Van der Elst, W., Molenberghs, G., Hilgers, R., & Heussen, N. (2015). Estimating the reliability of repeatedly measured endpoints based on linear mixed-effects models. A tutorial. Submitted.

See Also

WS.Corr.Mixed

Examples

data(Example.Data)

# Code predictors for time
Example.Data$Time2 <- Example.Data$Time**2
Example.Data$Time3 <- Example.Data$Time**3
Example.Data$Time3_log <- (Example.Data$Time**3) * (log(Example.Data$Time))

# model 1
Model1 <- WS.Corr.Mixed(
Fixed.Part=Outcome ~ Time2 + Time3 + Time3_log + as.factor(Cycle) 
+ as.factor(Condition), Random.Part = ~ 1|Id, 
Dataset=Example.Data, Model=1, Id="Id", 
Number.Bootstrap = 0, Seed = 12345)

# model 2
Model2 <- WS.Corr.Mixed(
Fixed.Part=Outcome ~ Time2 + Time3 + Time3_log + as.factor(Cycle) 
+ as.factor(Condition), Random.Part = ~ 1|Id, 
Correlation=corGaus(form= ~ Time, nugget = TRUE),
Dataset=Example.Data, Model=2, Id="Id", 
Number.Bootstrap = 0, Seed = 12345)

# model 3
Model3 <- WS.Corr.Mixed(
  Fixed.Part=Outcome ~ Time2 + Time3 + Time3_log + as.factor(Cycle) 
  + as.factor(Condition), Random.Part = ~ 1 + Time|Id, 
  Correlation=corGaus(form= ~ Time, nugget = TRUE),
  Dataset=Example.Data, Model=3, Id="Id", 
  Number.Bootstrap = 0, Seed = 12345)

# compare models 1 and 2
Model.Fit(Model.1=Model1, Model.2=Model2)

# compare models 2 and 3
Model.Fit(Model.1=Model2, Model.2=Model3)