observations_MET: Minimum-effect tests using observations and known measurement...

In mladenjovanovic/bmbstats: Bootstrap Magnitude-Based Statistics

Description

Minimum-effect tests using observations and known measurement error

Usage

observations_MET(
  observations,
  observations_label = NULL,
  measurement_error = 0,
  df = Inf,
  SESOI_lower = 0,
  SESOI_upper = 0,
  alpha = 0.05,
  confidence = 0.95
)

Arguments

observations	Numeric vector of observed scores
observations_label	Vector used for labeling observations. Default is NULL
measurement_error	Estimated SD of the random error. Default is 0
df	Degrees of freedom from the reliability study where measurement_error is estimated. Default is Inf, which implies the use of normal distribution
SESOI_lower	Lower smallest effect size of interest threshold
SESOI_upper	Upper smallest effect size of interest threshold
alpha	Numeric value for the alpha (Type I error). Default is 0.05
confidence	Default is 0.95

Examples

data("bench_press_data")
obs_MET <- observations_MET(
  bench_press_data$Change,
  SESOI_lower = -5,
  SESOI_upper = 5,
  measurement_error = 2.5,
  alpha = 0.05
)

obs_MET
plot(obs_MET)

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