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Implicit Association Test - Recoding Free (IAT-RF)
Main Inquisit programming: Sean Draine (email@example.com)
last updated: 10-04-2019 by K. Borchert (firstname.lastname@example.org) for Millisecond Software, LLC
Script Copyright © 10-04-2019 Millisecond Software
BACKGROUND INFO: General IAT and IAT-RF
The Implicit Association Task (Greenwald, McGhee, & Schwartz, 1998) is a widely-used cognitive-behavioral paradigm
that measures the strength of automatic (implicit) associations between concepts in people’s minds relying
on latency measures in a simple sorting task.
In the typical IAT procedure, participants are asked to sort attributes (e.g. "joyful"; "tragic") and target items
(e.g "daisy" vs. "wasp") into predetermined categories via keystroke presses. The basic task is to press a left key (E)
if an item (e.g. "joyful") belongs to the category presented on the left (e.g. "Good") and to press the right key (I)
if the word (e.g. "tragic") belongs to the category ("Bad") presented on the right. For the actual test, participants
are asked to sort categories into the paired/combined categories (e.g. "Flower OR Good" on the left vs. "Insect OR Bad" on the right).
Pairings are reversed for a second test (e.g. "Insects OR Good" on the left vs. "Flowers OR Bad" on the right).
The traditional IAT procedure tests category pairings in a blocked format (test 1 vs. test2 with reversed pairings)
and requires a potential recoding of information inbetween the category switch from test 1 to test 2.
Rothermund et al (2009) suggest that this potential recoding of information has a strong effect on the IAT results
and propose an alteration to the traditional IAT procedure to eliminate recoding. The proposed change is to test category
pairings in a within-subjects mixed design: In the recoding free IAT (IAT-RF), category pairings can switch from trial to trial
within the same block.
The strength of an association between concepts in IATs is measured by the standardized mean difference score of
the 'hypothesis-inconsistent' pairings and 'hypothesis-consistent' pairings (d-score) (Greenwald, Nosek, & Banaji, 2003).
In general, the higher the d-score the stronger is the association between the 'hypothesis-consistent' pairings
(decided by researchers). Negative d-scores suggest a stronger association between the 'hypothesis-inconsistent' pairings.
Inquisit calculates d-scores using the improved scoring algorithm as described in Greenwald et al (2003).
Error trials are handled by requiring respondents to correct their responses according to recommendation (p.214).
D-scores obtained with this script:
Positive d-scores: support a stronger association between 'Flowers-Good' and 'Insects-Bad' than for the opposite pairings
Negative d-scores: support a stronger association between 'Insects-Good' and 'Flowers-Bad' than for the opposite pairings
Greenwald, A. G., McGhee, D. E., & Schwartz, J. K. L. (1998). Measuring individual differences in implicit cognition:
The Implicit Association Test. Journal of Personality and Social Psychology, 74, 1464-1480.
Greenwald, A. G., Nosek, B. A., & Banaji, M. R. (2003). Understanding and Using the Implicit Association Test:
I. An Improved Scoring Algorithm. Journal of Personality and Social Psychology, 85, 197-216.
Rothermund, K., Teige-Mocigemba, S., Gast, A., & Wentura, D. (2009). Eliminating the influence of recoding in the Implicit
Association Test: The Recoding-Free Implicit Association Test (IAT-RF). Quarterly Journal of Experimental Psychology, 62,
Participants are asked to categorize attributes (e.g. "joyful"; "tragic") and target items (e.g "daisy" vs. "wasp")
into predetermined categories via keystroke presses. The basic task is to press a left key (E) if an item (e.g. "joyful")
belongs to the category presented on the left (e.g. "Good") and to press the right key (I) if the word (e.g. "tragic")
belongs to the category ("Bad") presented on the right.
For practice, participants sort items into the target categories "Flowers vs. Insects" and the attribute categories "Good vs. Bad".
For the test, participants are asked to sort categories into the paired/combined categories (e.g.
"Flower OR Good" on the left vs. "Insect OR Bad" on the right). Pairings are reversed for a second test
(e.g. "Insects OR Good" on the left vs. "Flowers OR Bad" on the right). Order is counterbalanced by groupnumber.
the default set-up of the script takes appr. 5 minutes to complete
DATA FILE INFORMATION
The default data stored in the data files are:
(1) Raw data file: 'iat_rf_raw*.iqdat' (a separate file for each participant)
build: The specific Inquisit version used (the 'build') that was run
computer.platform: the platform the script was run on (win/mac/ios/android)
date, time, date and time script was run
subject, group, with the current subject/groupnumber
Note: odd/even groupnumbers balance the order in which
hypothesis-compatible/incompatible blocks are run
odd = compatible - incompatible
even = incompatible - compatible
script.sessionid: with the current session id
blockcode, blocknum: the name and number of the current block (built-in Inquisit variable)
trialcode, trialnum: the name and number of the currently recorded trial (built-in Inquisit variable)
Note: trialnum is a built-in Inquisit variable; it counts all trials run;
even those that do not store data to the data file such as feedback trials
values.item: the presented item
response: the final trial response (scancodes of the keys pressed)
18 = E
23 = I
57 = spacebar press
Note: script saves the final and -by design- correct response for each trial
correct: the accuracy of the initial response
0 = initial response was incorrect and needed to be corrected
1 = initial response is correct
latency: the latency of the final (correct) response in ms; measured from onset of stim
(2) Summary data file: 'iat_rf_summary*.iqdat' (a separate file for each participant)
computer.platform: the platform the script was run on (win/mac/ios/android)
script.startdate: date script was run
script.starttime: time script was started
script.subjectid: assigned subject id number
script.groupid: assigned group id number
script.sessionid: assigned session id number
script.elapsedtime: time it took to run script (in ms); measured from onset to offset of script
script.completed: 0 = script was not completed (prematurely aborted);
1 = script was completed (all conditions run)
expressions.d: overall d-score; main DV
D-score <= -0.65 => "a strong" preference for hypothesis-NONconforming pairings
D-score < -0.35 => "a moderate" preference for hypothesis-NONconforming pairings
D-score < -0.15 => "a slight" preference for hypothesis-NONforming pairings
-0.15 <= D-score <= 0.15 "little to no" preference
D-score > 0.15 => "a slight" preference for hypothesis-conforming pairings
D-score > 0.35 => "a moderate" preference for hypothesis-conforming pairings
D-score >= 0.65 => "a strong" preference for hypothesis-conforming pairings
expressions.percentcorrect: the overall percent correct score of initial responses in test trials of D-score qualifying latencies
expressions.propRT300: the proportion of response latencies < 300ms
expressions.excludeCriteriaMet:1 = yes, exclusion supported per Greenwald et al (2003, p.214, Table 4):
More than 10% of all response latencies are faster than 300ms
0 = otherwise
Hypothesis-consistent pairings vs. hypothesis-inconsistent pairings; tested within-subjects in a mixed design
1. Attribute sorting training: 16 trials; 8 positive; 8 negative; order is randomly determined
2. Target Category sorting training: 16 trials, 4 flowers left, 4 flowers right, 4 insects left, 4 insects right; order is randomly determined
3. Combined category practice: 32 trials, 16 flowers-good left (insect-bad right); 16 insect-good left (flower-bad right); order is randomly determined
4. Combined test: 128 trials, 64 flowers-good left (insect-bad right); 16 insect-good left (flower-bad right); order is randomly determined
Each trial starts with a fixation cross (1) that is presented for 500ms.
Stimuli can be edited under section Editable Stimuli
Instructions can be edited under section Editable Instructions
check below for (relatively) easily editable parameters, stimuli, instructions etc.
Keep in mind that you can use this script as a template and therefore always "mess" with the entire code
to further customize your experiment.
The parameters you can change are:
/showsummaryfeedback: set parameter showsummaryfeedback = true to display summary feedback to participants at the end (default)
set parameter showsummaryfeedback = false if no summary feedback should be presented to participants