crawford.test: Crawford-Garthwaite (2007) Bayesian test for single-case...

In neuropsychology/psycho.R: Efficient and Publishing-Oriented Workflow for Psychological Science

Description

Neuropsychologists often need to compare a single case to a small control group. However, the standard two-sample t-test does not work because the case is only one observation. Crawford and Garthwaite (2007) demonstrate that the Bayesian test is a better approach than other commonly-used alternatives. .

Usage

crawford.test(
  patient,
  controls = NULL,
  mean = NULL,
  sd = NULL,
  n = NULL,
  CI = 95,
  treshold = 0.1,
  iter = 10000,
  color_controls = "#2196F3",
  color_CI = "#E91E63",
  color_score = "black",
  color_size = 2,
  alpha_controls = 1,
  alpha_CI = 0.8
)

Arguments

patient	Single value (patient's score).
controls	Vector of values (control's scores).
mean	Mean of the control sample.
sd	SD of the control sample.
n	Size of the control sample.
CI	Credible interval bounds.
treshold	Significance treshold.
iter	Number of iterations.
color_controls	Color of the controls distribution.
color_CI	Color of CI distribution.
color_score	Color of the line representing the patient's score.
color_size	Size of the line representing the patient's score.
alpha_controls	Alpha of the CI distribution.
alpha_CI	lpha of the controls distribution.

Details

The p value obtained when this test is used to test significance also simultaneously provides a point estimate of the abnormality of the patient’s score; for example if the one-tailed probability is .013 then we know that the patient’s score is significantly (p < .05) below the control mean and that it is estimated that 1.3

Author(s)

Dominique Makowski

Examples

library(psycho)

crawford.test(patient = 125, mean = 100, sd = 15, n = 100)
plot(crawford.test(patient = 80, mean = 100, sd = 15, n = 100))

crawford.test(patient = 10, controls = c(0, -2, 5, 2, 1, 3, -4, -2))
test <- crawford.test(patient = 7, controls = c(0, -2, 5, -6, 0, 3, -4, -2))
plot(test)

neuropsychology/psycho.R documentation built on Jan. 25, 2021, 7:59 a.m.