broom (version 0.4.5)

lmodel2_tidiers: Tidiers for linear model II objects from the lmodel2 package

Description

Tidy or glance an lmodel2 object. An lmodel2 represents model II simple linear regression, where both variables in the regression equation are random.

Usage

# S3 method for lmodel2
tidy(x, ...)
# S3 method for lmodel2
glance(x, ...)

Arguments

x

lmodel2 object

...

Extra arguments, not used

Value

All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.

tidy returns a data frame with one row for each combination of method (OLS/MA/SMA/RMA) and term (always Intercept/Slope). Its columns are:

method

Either OLS/MA/SMA/RMA

term

Either "Intercept" or "Slope"

estimate

Estimated coefficient

conf.low

Lower bound of 95% confidence interval

conf.high

Upper bound of 95% confidence interval

glance returns a one-row data frame with columns

r.squared

OLS R-squared

p.value

OLS parametric p-value

theta

Angle between OLS lines lm(y ~ x) and lm(x ~ y)

H

H statistic for computing confidence interval of major axis slope

Details

Note that unlike linear regression, there are always only two terms in an lmodel2: Intercept and Slope. Furthermore, these are computed by four methods: OLS (ordinary least squares), MA (major axis), SMA (standard major axis), and RMA (ranged major axis). See the lmodel2 documentation for more.

Note that there is no augment method for lmodel2 objects because lmodel2 does not provide a predict or residuals method (and since when both observations are random, fitted values and residuals have a less clear meaning).

Examples

# NOT RUN {
if (require("lmodel2", quietly = TRUE)) {
  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))
}

# }