report (version 0.1.0)

report.stanreg: Bayesian Models Report

Description

Create a report of Bayesian models.

Usage

# S3 method for stanreg
report(
  model,
  interpretation = "default",
  ci = 0.89,
  standardize = "smart",
  standardize_robust = FALSE,
  centrality = "median",
  dispersion = FALSE,
  ci_method = "hdi",
  test = c("pd", "rope"),
  rope_range = "default",
  rope_ci = 1,
  bf_prior = NULL,
  diagnostic = c("ESS", "Rhat"),
  performance_metrics = "all",
  ...
)

Arguments

model

Model object.

interpretation

Interpret the standardized parameters using a set of rules. Default corresponds to "cohen1988" for linear models and "chen2010" for logistic models.

ci

Confidence Interval (CI) level. Default to 0.95 (95%).

standardize

The method used for standardizing the parameters. Can be "refit", "posthoc", "smart", "basic" or NULL (default) for no standardization. See 'Details' in standardize_parameters. Note that robust estimation (i.e. robust=TRUE) of standardized parameters only works when standardize="refit".

standardize_robust

Logical, if TRUE, robust standard errors are calculated (if possible), and confidence intervals and p-values are based on these robust standard errors.

centrality

The point-estimates (centrality indices) to compute. Character (vector) or list with one or more of these options: "median", "mean", "MAP" or "all".

dispersion

Logical, if TRUE, computes indices of dispersion related to the estimate(s) (SD and MAD for mean and median, respectively).

ci_method

The type of index used for Credible Interval. Can be "HDI" (default, see hdi), "ETI" (see eti) or "SI" (see si).

test

The indices of effect existence to compute. Character (vector) or list with one or more of these options: "p_direction" (or "pd"), "rope", "p_map", "equivalence_test" (or "equitest"), "bayesfactor" (or "bf") or "all" to compute all tests. For each "test", the corresponding bayestestR function is called (e.g. rope or p_direction) and its results included in the summary output.

rope_range

ROPE's lower and higher bounds. Should be a list of two values (e.g., c(-0.1, 0.1)) or "default". If "default", the bounds are set to x +- 0.1*SD(response).

rope_ci

The Credible Interval (CI) probability, corresponding to the proportion of HDI, to use for the percentage in ROPE.

bf_prior

Distribution representing a prior for the computation of Bayes factors / SI. Used if the input is a posterior, otherwise (in the case of models) ignored.

diagnostic

Diagnostic metrics to compute. Character (vector) or list with one or more of these options: "ESS", "Rhat", "MCSE" or "all".

performance_metrics

See model_performance.

...

Arguments passed to or from other methods. For instance, when bootstrap = TRUE, arguments like ci_method are passed down to describe_posterior.

Value

A list-object of class report, which contains further list-objects with a short and long description of the model summary, as well as a short and long table of parameters and fit indices.

See Also

table_short or text_short to access the related content of the report-object.

Examples

# NOT RUN {
library(report)
if (require("rstanarm")) {
  model <- stan_glm(Sepal.Length ~ Petal.Length * Species,
    data = iris, iter = 250, refresh = 0
  )
  r <- report(model)
  text_short(r)
  text_long(r)
  table_short(r)
  table_long(r)
  model <- stan_lmer(Sepal.Length ~ Petal.Length + (1 | Species),
    data = iris, iter = 100, refresh = 0
  )
  report(model)
}
# }