Prediction of model averaged linear mixed models
Function to perform prediction for model averaged linear mixed models based on the weight selection criterion as proposed by Zhang et al.(2014)
predictMA(object, new.data)
object |
A object created by the model averaging function. |
new.data |
Object that contains the data on which the prediction is to be based on. |
An object that containing predictions that are calculated on the basis of dataset and the underlying averaged model.
Benjamin Saefken & Rene-Marcel Kruse
Greven, S. and Kneib T. (2010) On the behaviour of marginal and conditional AIC in linear mixed models. Biometrika 97(4), 773-789.
data(Orthodont, package = "nlme")
models <- list(
model1 <- lmer(formula = distance ~ age + Sex + (1 | Subject) + age:Sex,
data = Orthodont),
model2 <- lmer(formula = distance ~ age + Sex + (1 | Subject),
data = Orthodont),
model3 <- lmer(formula = distance ~ age + (1 | Subject),
data = Orthodont),
model4 <- lmer(formula = distance ~ Sex + (1 | Subject),
data = Orthodont))
foo <- modelAvg(models = models)
predictMA(foo, new.data = Orthodont)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.