Visually compare the marginals of multiple models and/or datasets.
Source:R/brm_plot_compare.R
brm_plot_compare.RdVisually compare the marginals of multiple models and/or datasets.
Usage
brm_plot_compare(
...,
marginal = "response",
compare = "source",
axis = "time",
facet = c("group", "subgroup")
)Arguments
- ...
Named
tibbles of marginals posterior summaries frombrm_marginal_summaries()and/orbrm_marginal_data().- marginal
Character of length 1, which kind of marginal to visualize. Must be a value in the
marginalcolumn of the suppliedtibbles in the...argument. Only applies to MCMC output, the data is always on the scale of the response variable.- compare
Character of length 1 identifying the variable to display using back-to-back interval plots of different colors. This is the primary comparison of interest. Must be one of
"source"(the source of the marginal summaries, e.g. a model or dataset),"time"or"group"(in the non-subgroup case). Can also be"subgroup"if all the marginal summaries are subgroup-specific. The value must not be inaxisorfacet.- axis
Character of length 1 identifying the quantity to put on the horizontal axis. Must be be one of
"source"(the source of the marginal summaries, e.g. a model or dataset),"time", or"group"(in the non-subgroup case). If the marginals are subgroup-specific, thenaxiscan also be"subgroup". The value must not be incompareorfacet.- facet
Character vector of length 1 or 2 with quantities to generate facets. Each element must be
"source"(the source of the marginal summaries, e.g. a model or dataset),"time","group", or"subgroup", andc(axis, facet)must all have unique elements."subgroup"is automatically removed if not all the marginal summaries have a subgroup column. Iffacethas length 1, then faceting is wrapped. Iffacethas length 2, then faceting is in a grid, and the first element is horizontal facet.
Details
By default, brm_plot_compare() compares multiple models
and/or datasets side-by-side. The compare argument selects the primary
comparison of interest, and arguments axis and facet control
the arrangement of various other components of the plot.
The subgroup variable is automatically included if and only if
all the supplied marginal summaries have a subgroup column.
See also
Other visualization:
brm_plot_draws()
Examples
if (identical(Sys.getenv("BRM_EXAMPLES", unset = ""), "true")) {
set.seed(0L)
data <- brm_data(
data = brm_simulate_simple()$data,
outcome = "response",
group = "group",
time = "time",
patient = "patient",
reference_group = "group_1",
reference_time = "time_1"
)
formula <- brm_formula(
data = data,
baseline = FALSE,
baseline_time = FALSE
)
tmp <- utils::capture.output(
suppressMessages(
suppressWarnings(
model <- brm_model(
data = data,
formula = formula,
chains = 1,
iter = 100,
refresh = 0
)
)
)
)
draws <- brm_marginal_draws(data = data, formula = formula, model = model)
suppressWarnings(summaries_draws <- brm_marginal_summaries(draws))
summaries_data <- brm_marginal_data(data)
brm_plot_compare(
model1 = summaries_draws,
model2 = summaries_draws,
data = summaries_data
)
brm_plot_compare(
model1 = summaries_draws,
model2 = summaries_draws,
marginal = "difference"
)
}