Calculate area under the selection weight function from a selmodel object

Summarize the strength of selection by calculating the area under the selection weight function a selmodel object (excluding the area with weight fixed at 1). If the object has bootstrap replications, then a confidence interval will also be calculated.

Usage

p_area(object, CI_type = NULL, conf_level = NULL, warn = TRUE)

Arguments

object: fitted model of class "selmodel".
CI_type: character string specifying the type of confidence interval to calculate, with options as in "selection_model". If NULL (the default), it will be inherited from object.
conf_level: desired coverage level for confidence intervals. If NULL (the default), it will be inherited from object, which has a default value of .95.
warn: logical controlling whether warnings are displayed, with a default of TRUE.

Value

A data.frame containing the estmated area under the selection weight function. If the input object includes bootstraps, then the returned data.frame also includes bootstrap confidence interval(s) for the area under the selection weight function.

Examples


beta_noboot <- selection_model(
  data = practice_facilitation,
  yi = SMD,
  sei = SE,
  selection_type = "beta",
  steps = c(0.025,0.975)
)

p_area(beta_noboot)
#>    param        Est
#> 1 p-area 0.09652784

step_boot <- selection_model(
  data = self_control,
  yi = g,
  sei = se_g,
  cluster = studyid,
  selection_type = "step",
  steps = c(0.025,0.50),
  estimator = "ARGL",
  bootstrap = "multinomial",
  CI_type = "normal",
  R = 9L
)

p_area(step_boot)
#>    param       Est       SE bootstraps normal_lower normal_upper
#> 1 p-area 0.5989296 4.327653          9    -9.202823     7.761264