bt_test_mf | R Documentation |
Basic function for running the Bayesian t-tests included in the main analyses
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"
)
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 |
na.rm |
Whether NAs should be removed, default to |
paired |
Whether the t-test refers to dependent (i.e., paired) or to independent sample(s). Default to |
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 |
dv |
name of the measured conditioned response. Default to |
exclusion |
Name of the data reduction procedure used. Default to |
cut_off |
cut off Name of the cut_off applied. Default to |
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.
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
# 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)
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