AATtools (version 0.0.3)

Reliability and Scoring Routines for the Approach-Avoidance Task

Description

Compute approach bias scores using different scoring algorithms, compute bootstrapped and exact split-half reliability estimates, and compute confidence intervals for individual participant scores.

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Version

Install

install.packages('AATtools')

Monthly Downloads

548

Version

0.0.3

License

GPL-3

Maintainer

Sercan Kahveci

Last Published

August 16th, 2024

Functions in AATtools (0.0.3)

splitrel

Split Half-Based Reliability Coefficients

q_reliability

Compute psychological experiment reliability

covrel

Covariance Matrix-Based Reliability Coefficients

correlation-tools

Correlation tools

erotica

AAT examining approach bias for erotic stimuli

covEM

Covariance matrix computation with multiple imputation

aat_splithalf

Compute the bootstrapped split-half reliability for approach-avoidance task data

aat_covreliability

Compute a dataset's reliability from its covariance matrix

aat_stimulusscores

Compute stimulus-specific bias scores Computes mean single-difference scores (push - pull) for each stimulus.

Preprocessing

Pre-processing rules

Algorithms

AAT score computation algorithms

cormean

Compute a minimally biased average of correlation values

aat_simulate

Simulate AAT datasets and predict parameters

aat_compute

Compute simple AAT scores

aat_bootstrap

Compute bootstrapped approach-bias scores

aat_stimulus_rest

Compute stimulus-rest correlations of double-difference scores This function provides a statistic that can give an indication of how deviant the responses to specific stimuli are, in comparison to the rest of the stimulus set. The algorithm computes stimulus-rest correlations of stimulus-specific double-difference scores. It takes single-difference approach-avoidance scores for each stimulus, and computes every possible subtraction between individual stimuli from both stimulus categories. It then computes correlations between every such subtraction of stimuli on one hand, and the mean double difference score of all other stimuli. Stimulus-rest correlations are then computed by averaging every such subtraction-rest correlation involving a specific stimulus.