Learn R Programming

gratia (version 0.8.2)

difference_smooths: 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 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

Run this code

load_mgcv()
# \dontshow{
op <- options(pillar.sigfig = 3, cli.unicode = FALSE)
# }
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)
options(op)

Run the code above in your browser using DataLab