validity_analysis: Validity Analysis

In mladenjovanovic/bmbstats: Bootstrap Magnitude-Based Statistics

Description

validity_analysis represents a wrapper function for the bmbstats function. validity_analysis runs the bootstrap validity analysis of the data data frame using estimator_function to return the estimators

Usage

validity_analysis(
  data,
  criterion,
  practical,
  SESOI_lower = SESOI_lower_validity_func,
  SESOI_upper = SESOI_upper_validity_func,
  estimator_function = validity_estimators,
  control = model_control(),
  na.rm = FALSE
)

Arguments

data	Data frame
criterion	Character vector indicating column name in the data
practical	Character vector indicating column name(s) in the data
SESOI_lower	Function or numeric scalar. Default is SESOI_lower_validity_func
SESOI_upper	Function or numeric scalar. Default is SESOI_upper_validity_func
estimator_function	Function for providing validity estimators. Default is validity_estimators
control	Control object returned from model_control function. Use boot_type, boot_samples, boot_strata, and confidence to setup bootstrap.
na.rm	Should NAs be removed? Default is FALSE

Value

Object of class bmbstats

Examples

data("agreement_data")

val_analysis <- validity_analysis(
  data = agreement_data,
  criterion = "Criterion_score.trial1",
  practical = "Practical_score.trial1",
  control = model_control(
    boot_type = "perc",
    boot_samples = 1000,
    seed = 1667
  )
)

val_analysis

plot(val_analysis)

mladenjovanovic/bmbstats documentation built on Aug. 5, 2020, 4:20 p.m.