multifear (version 0.1.5)

bt_test_mf: bt_test_mf

Description

Basic function for running the Bayesian t-tests included in the main analyses

Usage

bt_test_mf(
  cs1,
  cs2,
  data,
  subj,
  group = NULL,
  na.rm = FALSE,
  paired = TRUE,
  rscale = "medium",
  phase = "acquisition",
  dv = "scr",
  exclusion = "full data",
  cut_off = "full data"
)

Value

A tibble with the following column names:

x: the name of the independent variable (e.g., cs)

y: the name of the dependent variable as this defined in the dv argument

exclusion: see exclusion argument

model: the model that was run (e.g., t-test)

controls: ignore this column for this test

method: the model that was run

p.value: irrelevant here

effect.size: irrelevant here

effect.size.ma: irrelevant here

estimate: the estimate of the test run

statistic: the t-value

conf.low: the lower confidence interval for the estimate

conf.high: the higher confidence interval for the estimate

framework: were the data analysed within a NHST or Bayesian framework?

data_used: a list with the data used for the specific test

Arguments

cs1

The column name(s) of the conditioned responses for the first conditioned stimulus

cs2

The column name(s) of the conditioned responses for the second conditioned stimulus

data

A data frame containing all the relevant columns for the analyses

subj

The name of the column including the participant numbers. Unique numbers are expected

group

the name of the group, if included, default to NULL

na.rm

Whether NAs should be removed, default to FALSE

paired

Whether the t-test refers to dependent (i.e., paired) or to independent sample(s). Default to TRUE

rscale

r scale to be used in the prior of the alternative hypothesis, default to "medium".

phase

The conditioned phase that the analyses refer to. Accepted values are acquisition, acq, extinction, or ext

dv

name of the measured conditioned response. Default to "SCR"

exclusion

Name of the data reduction procedure used. Default to full data

cut_off

cut off Name of the cut_off applied. Default to full data

Details

This is a wrapper function function around the BayesFactor::ttestBF(), running multiple Bayesian t-tests. Similar to the t_test_mf function, the function will run different t-tests based on the phase that the t-tests refer to. So, in case of the acquisition phase, there will be a t-test of differences and positive differences, whereas for the extinction phase a t-test for differences and negative differences.

Examples

# Load example data
data(example_data)

# Paired sample t-tests
bt_test_mf(cs1 = "CSP1", cs2 = "CSM1", subj = "id", data = example_data)

# Independent  sample t-tests
bt_test_mf(cs1 = "CSP1", cs2 = "CSM1", subj = "id",  group = "group", data = example_data)