emmeans.sdmTMB: Estimated marginal means with the 'emmeans' package with...

In sdmTMB: Spatial and Spatiotemporal SPDE-Based GLMMs with 'TMB'

Estimated marginal means with the emmeans package with sdmTMB

Description

Methods for using the emmeans package with sdmTMB. The emmeans package computes estimated marginal means for the fixed effects.

References

https://aosmith.rbind.io/2019/03/25/getting-started-with-emmeans/

Examples

mesh <- make_mesh(pcod_2011, c("X", "Y"), cutoff = 20)
fit <- sdmTMB(
  present ~ as.factor(year),
  data = pcod_2011, mesh = mesh,
  family = binomial()
)
fit
emmeans::emmeans(fit, ~ year)
emmeans::emmeans(fit, pairwise ~ year)
emmeans::emmeans(fit, pairwise ~ year, type = "response")
emmeans::emmeans(fit, pairwise ~ year, adjust = "none")

e <- emmeans::emmeans(fit, ~ year)
plot(e)

e <- emmeans::emmeans(fit, pairwise ~ year)
confint(e)
summary(e, infer = TRUE)
as.data.frame(e)

# interaction of factor with continuous predictor:
fit2 <- sdmTMB(
  present ~ depth_scaled * as.factor(year),
  data = pcod_2011, mesh = mesh,
  family = binomial()
)
fit2
# slopes for each level:
emmeans::emtrends(fit2, ~ year, var = "depth_scaled")
# test difference in slopes:
emmeans::emtrends(fit2, pairwise ~ year, var = "depth_scaled")
emmeans::emmip(fit2, year ~ depth_scaled,
  at = list(depth_scaled = seq(-2.5, 2.5, length.out = 50)), CIs = TRUE)

sdmTMB documentation built on June 22, 2024, 10:48 a.m.