Plot effect estimates by exposure time for one or more models.

Usage

plot_effect_curves(
  ...,
  labels = NA,
  facet_nrow = 1,
  continuous = FALSE,
  resolution = 0.1
)

Arguments

...: One or more objects of class "sw_analysis" returned by analyze.
labels: A character vector of length equal to the length of list(...), representing plot labels. Only used if length(list(...))>1.
facet_nrow: Number of rows for displaying plots using ggplot2::facet_wrap().
continuous: Logical; if TRUE, models fit with Natural Cubic Splines (exp_time = "NCS") will be evaluated and plotted as smooth, continuous curves. Models using discrete exposure times (e.g., ETI, DCT) will remain discrete.
resolution: Numeric; the step size for generating the continuous curve. Defaults to 0.1. Only relevant if continuous = TRUE.

Value

A plot of the effect curve for each "sw_analysis" object passed to the function.

Examples

# Load data
test_data <- load_data(time ="period", cluster_id = "cluster", individual_id = NULL,
treatment = "trt", outcome = "outcome_cont", data = sw_data_example)

# \donttest{
IT_model <- analyze(dat = test_data, method = "mixed", estimand_type = "TATE",
estimand_time = c(1, 4), exp_time = "IT")
ETI_model <- analyze(dat = test_data, method = "mixed", estimand_type = "TATE",
estimand_time = c(1, 4), exp_time = "ETI")
NCS_4_model <- analyze(dat = test_data, method = "mixed", estimand_type = "TATE",
estimand_time = c(1, 4), exp_time = "NCS", advanced = params(n_knots_exp = 4))

# Plot discrete models
plot_effect_curves(IT_model, NCS_4_model, ETI_model, facet_nrow = 1)

# Plot continuous NCS model alongside discrete models
plot_effect_curves(IT_model, NCS_4_model, ETI_model, facet_nrow = 1, continuous = TRUE)
# }