update_nested: Update Nested Models in Hierarchical Regression.

In petersenlab: A Collection of R Functions by the Petersen Lab

Update Nested Models in Hierarchical Regression.

Description

Wrapper function to ensure the same observations are used for each updated model as were used in the first model.

Usage

update_nested(object, formula., ..., evaluate = TRUE)

Arguments

object	model object to update
formula.	updated model formula
...	further parameters passed to the fitting function
evaluate	whether to evaluate the model. One of: TRUE or FALSE

Details

Convenience wrapper function to ensure the same observations are used for each updated model as were used in the first model, to ensure comparability of models.

Value

lm model

See Also

https://stackoverflow.com/a/37341927

https://stackoverflow.com/a/37416336

https://stackoverflow.com/a/47195348

Other multipleRegression: lmCombine(), plot2WayInteraction(), ppPlot(), semPlotInteraction()

Examples

# Prepare Data
data("mtcars")

dat <- mtcars

# Create some missing values in mtcars
dat[1, "wt"] <- NA
dat[5, "cyl"] <- NA
dat[7, "hp"] <- NA

m1 <- lm(mpg ~ wt + cyl + hp, data = dat)
m2 <- update_nested(m1, . ~ . - wt)  # Remove wt
m3 <- update_nested(m1, . ~ . - cyl) # Remove cyl
m4 <- update_nested(m1, . ~ . - wt - cyl) # Remove wt and cyl
m5 <- update_nested(m1, . ~ . - wt - cyl - hp) # Remove all three variables
# (i.e., model with intercept only)

anova(m1, m2, m3, m4, m5)

petersenlab documentation built on April 4, 2025, 12:22 a.m.