gg_slice {pammtools} | R Documentation |
Plot 1D (smooth) effects
Description
Flexible, high-level plotting function for (non-linear) effects conditional on further covariate specifications and potentially relative to a comparison specification.
Usage
gg_slice(data, model, term, ..., reference = NULL, ci = TRUE)
Arguments
data |
Data used to fit the |
model |
A suitable model object which will be used to estimate the
partial effect of |
term |
A character string indicating the model term for which partial effects should be plotted. |
... |
Covariate specifications (expressions) that will be evaluated
by looking for variables in |
reference |
If specified, should be a list with covariate value pairs,
e.g. |
ci |
Logical. Indicates if confidence intervals for the |
Examples
ped <- tumor[1:200, ] %>% as_ped(Surv(days, status) ~ . )
model <- mgcv::gam(ped_status~s(tend) + s(age, by = complications), data=ped,
family = poisson(), offset=offset)
make_newdata(ped, age = seq_range(age, 20), complications = levels(complications))
gg_slice(ped, model, "age", age=seq_range(age, 20), complications=levels(complications))
gg_slice(ped, model, "age", age=seq_range(age, 20), complications=levels(complications),
ci = FALSE)
gg_slice(ped, model, "age", age=seq_range(age, 20), complications=levels(complications),
reference=list(age = 50))