modelbased (version 0.6.0)

estimate_slopes.stanreg: Estimate the slopes of a numeric predictor (over different factor levels)

Description

Estimate the slopes of a numeric predictor (over different factor levels)

Usage

# S3 method for stanreg
estimate_slopes(
  model,
  trend = NULL,
  levels = NULL,
  transform = "response",
  standardize = TRUE,
  standardize_robust = FALSE,
  ci = 0.95,
  centrality = "median",
  ci_method = "hdi",
  test = c("pd", "rope"),
  rope_range = "default",
  rope_ci = 1,
  ...
)

Arguments

model

A Bayesian model.

trend

A character vector indicating the name of the numeric variable for which to compute the slopes.

levels

A character vector indicating the variables over which the slope will be computed. If NULL (default), it will select all the remaining predictors.

transform

Can be "none" (default for contrasts), "response" (default for means), "mu", "unlink", "log". "none" will leave the values on scale of the linear predictors. "response" will transform them on scale of the response variable. Thus for a logistic model, "none" will give estimations expressed in log-odds (probabilities on logit scale) and "response" in terms of probabilities.

standardize

If TRUE, adds standardized differences or coefficients.

standardize_robust

Robust standardization through MAD (Median Absolute Deviation, a robust estimate of SD) instead of regular SD.

ci

Credible Interval (CI) level. Default to 0.89 (89%). See ci for further details.

centrality

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

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.

...

Arguments passed to or from other methods.

Examples

# NOT RUN {
library(modelbased)
# }
# NOT RUN {
if (require("rstanarm")) {
  model <- stan_glm(Sepal.Width ~ Species * Petal.Length, data = iris)
  estimate_slopes(model)
}
# }