Tidy a(n) lmodel2 object
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.
## S3 method for class 'lmodel2' tidy(x, ...)
x |
A |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
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").
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 |
Other lmodel2 tidiers:
glance.lmodel2()
if (requireNamespace("lmodel2", quietly = TRUE)) {
library(lmodel2)
data(mod2ex2)
Ex2.res <- lmodel2(Prey ~ Predators, data = mod2ex2, "relative", "relative", 99)
Ex2.res
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))
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