Validity estimators

validity_estimators provides validity estimators using the simple linear regression model, where criterion is the outcome variable, and practical is the predictor.

validity_estimators(
  data,
  criterion,
  practical,
  SESOI_lower = 0,
  SESOI_upper = 0,
  na.rm = FALSE
)

Arguments

data	Data frame
criterion	Character vector indicating column name in the data
practical	Character vector indicating column name in the data
SESOI_lower	Lower smallest effect size of interest threshold
SESOI_upper	Upper smallest effect size of interest threshold
na.rm	Should NAs be removed? Default is FALSE

Value

Named vector with validity estimators

Examples

data("agreement_data")

validity_estimators(
  data = agreement_data,
  criterion = "Criterion_score.trial1",
  practical = "Practical_score.trial1"
)
#>  SESOI lower  SESOI upper  SESOI range    Intercept        Slope          RSE 
#>    0.0000000    0.0000000    0.0000000   -3.9394072    0.9494885    0.8760378 
#>  Pearson's r    R Squared SESOI to RSE         PPER          SDC 
#>    0.9875619    0.9752786    0.0000000    0.0000000    1.8335682