id_plot_irf – idealstan

Generate Impulse Response Functions for Covariates

Description

This function will generate an impulse response function (IRF) for a given covariate. The IRF shows the marginal impact of a 1-unit change in the covariate on a person’s ideal point over time. To use this function, the vary_ideal_pts option in id_estimate must have received the ‘AR1’ option as IRFs are only available for the AR(1) auto-regressive model.

Usage

id_plot_irf(
  object,
  cov_name = NULL,
  label_high = "Liberal",
  label_low = "Conservative",
  pred_outcome = NULL,
  recalc_vals = F,
  include = NULL,
  time_calc = 10,
  time_label = "Time Points",
  line_type = 2,
  line_width = 1,
  line_alpha = 1,
  line_color = "red",
  ci_color = "black",
  ci_alpha = 0.5,
  use_ci = TRUE,
  high_quantile = 0.95,
  low_quantile = 0.05,
  calc_varying = T
)

Arguments

`object`	A fitted `idealstan` object
`cov_name`	The name of the covariate to plot. Leave blank to select from a list of available covariates
`label_high`	The character label for the upper end of the latent scale
`label_low`	The character label for the lower end of the latent scale
`pred_outcome`	For discrete models with more than 2 categories, or binary models with missing data, which outcome to predict. This should be a character value that matches what the outcome was coded as in the data passed to `id_make`.
`recalc_vals`	Whether to combine two variables into one through addition before computing IRFs. If `TRUE`, two names of parameters should be passed to `cov_name` or selected from the dialog list
`include`	A list of character names of person or group IDs for which to calculate IRFs
`time_calc`	The maximum number of time points over which to calculate the IRF
`time_label`	Character string specifying the type of time points (default is just `“Time Points”`)
`line_type`	The line type of the IRF line (see `ggplot2` documentation)
`line_width`	The line width of the IRF line (see `ggplot2` documentation)
`line_alpha`	The line alpha (transparency) of the IRF line (see `ggplot2` documentation)
`line_color`	The color of the IRF line (see `ggplot2` documentation)
`ci_color`	The color of the IRF credible interval (see `ggplot2` documentation)
`ci_alpha`	The alpha of the IRF credible interval (see `ggplot2` documentation)
`use_ci`	Whether or not to plot a credible interval around the lines
`high_quantile`	The upper limit of the posterior density to use for calculating credible intervals
`low_quantile`	The lower limit of the posterior density to use for calculating credible intervals
`calc_varying`	if `TRUE`, will calculate marginal effects of the covariates on each end of the latent scale (see vignette for more information)

Value

a ggplot2 object that can be further customized if necessary