tidy.lmodel2: Tidy a(n) lmodel2 object

View source: R/lmodel2-tidiers.R

tidy.lmodel2R Documentation

Tidy a(n) lmodel2 object

Description

Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.

Usage

## S3 method for class 'lmodel2'
tidy(x, ...)

Arguments

x

A lmodel2 object returned by lmodel2::lmodel2().

...

Additional arguments. Not used. Needed to match generic signature only. Cautionary note: Misspelled arguments will be absorbed in ..., where they will be ignored. If the misspelled argument has a default value, the default value will be used. For example, if you pass conf.lvel = 0.9, all computation will proceed using conf.level = 0.95. Two exceptions here are:

  • tidy() methods will warn when supplied an exponentiate argument if it will be ignored.

  • augment() methods will warn when supplied a newdata argument if it will be ignored.

Details

There are always only two terms in an lmodel2: "Intercept" and "Slope". These are computed by four methods: OLS (ordinary least squares), MA (major axis), SMA (standard major axis), and RMA (ranged major axis).

The returned p-value is one-tailed and calculated via a permutation test. A permutational test is used because distributional assumptions may not be valid. More information can be found in vignette("mod2user", package = "lmodel2").

Value

A tibble::tibble() with columns:

conf.high

Upper bound on the confidence interval for the estimate.

conf.low

Lower bound on the confidence interval for the estimate.

estimate

The estimated value of the regression term.

p.value

The two-sided p-value associated with the observed statistic.

term

The name of the regression term.

method

Either OLS/MA/SMA/RMA

See Also

tidy(), lmodel2::lmodel2()

Other lmodel2 tidiers: glance.lmodel2()

Examples



# load libraries for models and data
library(lmodel2)

data(mod2ex2)
Ex2.res <- lmodel2(Prey ~ Predators, data = mod2ex2, "relative", "relative", 99)
Ex2.res

# summarize model fit with tidiers + visualization
tidy(Ex2.res)
glance(Ex2.res)

# this allows coefficient plots with ggplot2
library(ggplot2)

ggplot(tidy(Ex2.res), aes(estimate, term, color = method)) +
  geom_point() +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high)) +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high))


broom documentation built on Aug. 30, 2022, 1:07 a.m.