difference_smooths: Differences of factor smooth interactions

In gratia: Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

Differences of factor smooth interactions

Description

Estimates pairwise differences (comparisons) between factor smooth interactions (smooths with a factor by argument) for pairs of groups defined by the factor. The group means can be optionally included in the difference.

Usage

difference_smooths(model, ...)

## S3 method for class 'gam'
difference_smooths(
  model,
  smooth,
  n = 100,
  ci_level = 0.95,
  data = NULL,
  group_means = FALSE,
  partial_match = TRUE,
  unconditional = FALSE,
  frequentist = FALSE,
  ...
)

Arguments

model	A fitted model.
...	arguments passed to other methods. Not currently used.
smooth	character; which smooth to compute differences for.
n	numeric; the number of points at which to evaluate the difference between pairs of smooths.
ci_level	numeric between 0 and 1; the coverage of credible interval.
data	data frame of locations at which to evaluate the difference between smooths.
group_means	logical; should the group means be included in the difference?
partial_match	logical; should smooth match partially against smooths? If partial_match = TRUE, smooth must only be a single string, a character vector of length 1. Unlike similar functions, the default here is TRUE because the intention is that users will be matching against factor-by smooth labels.
unconditional	logical; account for smoothness selection in the model?
frequentist	logical; use the frequentist covariance matrix?

Examples

load_mgcv()

df <- data_sim("eg4", seed = 42)
m <- gam(y ~ fac + s(x2, by = fac) + s(x0), data = df, method = "REML")

sm_dif <- difference_smooths(m, smooth = "s(x2)")
sm_dif

draw(sm_dif)

# include the groups means for `fac` in the difference
sm_dif2 <- difference_smooths(m, smooth = "s(x2)", group_means = TRUE)
draw(sm_dif2)

gratia documentation built on Feb. 16, 2023, 10:40 p.m.