lmhelprs (version 0.4.0)

hierarchical: Check Models Hierarchy

Description

Check a list of 'lm' objects to see whether they are be ordered in a way for doing hierarchical regression analysis.

Usage

hierarchical(...)

Value

If the models can be ordered in a hierarchical way, the output is a list of the original lm

outputs, sorted from the model with the smallest number of terms to the model with the largest number of terms. If the models cannot be ordered this way, NA is returned.

Arguments

...

The outputs of lm(), that is, one or more lm-class objects. The outputs of other model fitting functions may also be used, but should be used with cautions. Please refer to the "How it works" section in "Details."

Author

Shu Fai Cheung https://orcid.org/0000-0002-9871-9448

Details

Two models can be compared by hierarchical regression analysis if one model can be formed by adding one or more terms to the other model.

This function checks whether a list of lm outputs can be ordered from the simplest model to the most complex model, with a more complex model formed by adding one or more terms to a simpler model.

How it works

It extracts the terms in each model by stats::terms() and then extracts the labels of the terms by labels(). The labels are then used to determine the hierarchical order.

Therefore, in principle, this function can be used for the outputs of other model fitting functions as long as their outputs support the stats::terms() and the labels can be used to determine hierarchical order of two models.

See Also

stats::lm()

Examples

dat <- data_test1
lm1 <- lm(y ~ x1 + x2, dat)
lm2 <- lm(y ~ x1 + x2 + x3 + x4, dat)
lm3 <- lm(y ~ x1 + cat1 + cat2 + x2 + x3 + x4, dat)
lm4 <- lm(y ~ x1 + x2*x3 + x4, dat)

# The order of entry does not matter
hierarchical(lm1, lm4, lm2)

# The following three models yield NA
hierarchical(lm3, lm4, lm2)