summaryMA: Summary of model averaged linear mixed models

In cAIC4: Conditional Akaike Information Criterion for 'lme4' and 'nlme'

Description

summaryMA is a function used to produce result summaries of the model averaging approach.

Usage

summaryMA(object, randeff = FALSE)

Arguments

object	A object created by the model averaging function.
randeff	logical. Indicator whether the model averaged random effects should also be part of the output. The default setting is FALSE.

Value

Outputs a summary of the model averaged random and fixed effects, as well as the calculated weights of the individual candidate models.

Author(s)

Benjamin Saefken & Rene-Marcel Kruse

References

Greven, S. and Kneib T. (2010) On the behaviour of marginal and conditional AIC in linear mixed models. Biometrika 97(4), 773-789.

See Also

lme4-package, lmer

Examples

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)
summaryMA(foo)

cAIC4 documentation built on Sept. 22, 2021, 5:07 p.m.