User Manual for Inquisit's Multifactor Religion IAT

Return to the Multifactor Religion IAT page

___________________________________________________________________________________________________________________

Multi-Factor Implicit Association Test (IAT) - Religion
___________________________________________________________________________________________________________________

Main Inquisit programming: Sean Draine (seandr@millisecond.com)
last updated: 10-04-2019 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC

___________________________________________________________________________________________________________________
BACKGROUND INFO: Specific BIAT
___________________________________________________________________________________________________________________

The University of Washington has applied for patent on the BIAT method. The patent
is managed by Project Implicit. Both the University of Washington and Project Implicit
authorize free use of the BIAT method and published stimuli for scholarly research,
provided that reports of the research clearly identify any modifications made to the
BIAT and appropriately cite the present article. Please contact Project Implicit
(E-mail: feedback@projectimplicit.net) to request a license for commercial or other
nonscholarly use of the BIAT.

The brief IAT (BIAT) procedure is explained in detail in:

Sriram, N. & Anthony G. Greenwald, A.G (2009).The Brief Implicit Association Test.
Experimental Psychology, 56, 283–294. (see page. 285, Table 1 for an overview of the procedure)

___________________________________________________________________________________________________________________
BACKGROUND INFO: General IAT/BIAT
___________________________________________________________________________________________________________________

The Implicit Association Task (IAT: Greenwald, McGhee, & Schwartz, 1998) and the brief IAT (BIAT: Sriram & Greenwald, 2009)
are widely-used cognitive-behavioral paradigms that measure the strength of automatic (implicit) associations
between concepts in people’s minds relying on latency measures in simple sorting tasks.

The strength of an association between concepts 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 contrast 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).

Constrast D-scores obtained with this script:
Positive scores indicate a preference for the lefthand category
Negative scores indicate a preference for the righthand category

Example:
expressions.ABd (A is on the left; B is on the right) => A (=Christianity) vs. B (=Islam)
positive D-score indicates a preference for Christianity over Islam; negative D-score indicates a preference for Islam over Christianity.

Aggregate D-Scores:
Aggregate D-Scores are averaged D-Scores for each religion (see guidelines and explanations in Axt et al, 2014).
An aggregate D-score allows the evaluation of each religion compared to the others.
Positive scores = more favorable evaluation than the average one across all groups
Negative scores = less favorable evaluation than the average one across all groups

References:
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.

Sriram, N. & Anthony G. Greenwald, A.G (2009).The Brief Implicit Association Test.
Experimental Psychology, 56, 283–294. (see page. 285, Table 1 for an overview of the procedure)

Axt, J. R., Ebersole, C. R., & Nosek, B. A. (2014). The rules of implicit evaluation by race, religion, and age.
Psychological Science, Vol. 25(9), 1804–1815.

___________________________________________________________________________________________________________________
TASK DESCRIPTION
___________________________________________________________________________________________________________________
Participants are asked to categorize attributes (e.g. "joyful"; "tragic") and religious target items of 4 different
religious affiliations Christianity, Islam, Judaism, Buddhism (e.g "Church", "Koran", "Synagogue", "Karma")
into predetermined categories via keystroke presses.
For the test, participants are asked to sort categories into paired/combined categories (e.g.
"Christianity OR Good" on the left vs. "Anything else" on the right). The basic task is to press a left key (E) if an item
(e.g. "joyful" or "Church") belongs to the category presented on the left (e.g. "Christianity OR Good") and to press the right key (I)
if the word (e.g. "tragic" or "Koran") does not belong to the category on the left. Pairings are reversed for a second test
(e.g. "Islam OR Good" on the left vs. "Anything else" on the right). Each religious affiliation is tested against each other.
The order of the resulting 12 tests is determined randomly.*

*Axt et al (2014) used 24 different counterbalanced orders. Each racial/ethnic group appeared as a
target once every 4 blocks.

___________________________________________________________________________________________________________________
DURATION
___________________________________________________________________________________________________________________
the default set-up of the script takes appr. 7 minutes to complete

___________________________________________________________________________________________________________________
DATA FILE INFORMATION
___________________________________________________________________________________________________________________
The default data stored in the data files are:

(1) Raw data file: 'religioniat_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

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

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
stimulusnumber: the number of the current stimulus
stimulusitem: the currently presented item

Only meaningful for the last row of data in the raw data file (upon completion of IAT):

expressions.percentcorrect: the overall percent correct score of initial responses of test trials of D-score qualifying latencies

Suggested D-Score Interpretation:

D-score <= -0.65 => "a strong" preference for first letter (e.g. AB => strong preference for A)
D-score < -0.35 => "a moderate" preference for first letter
D-score < -0.15 => "a slight" preference for first letter
-0.15 <= D-score <= 0.15 "little to no" preference
D-score > 0.15 => "a slight" preference for second letter (e.g. AB => slight preference for B)
D-score > 0.35 => "a moderate" preference for second letter
D-score >= 0.65 => "a strong" preference for second letter

D-Scores Category Comparisons:

expressions.ABd: positive D-score indicates a preference for Christinity over Islam
negative D-score indicates a preference for Islam over Christinity

expressions.ACd: positive D-score indicates a preference for Christinity over Judaism
negative D-score indicates a preference for Judaism over Christinity

expressions.ADd: positive D-score indicates a preference for Christinity over Panda Cups
negative D-score indicates a preference for Panda Cups over Christinity

expressions.BCd: positive D-score indicates a preference for Islam over Judaism
negative D-score indicates a preference for Judaism over Islam

expressions.BDd: positive D-score indicates a preference for Islam over Panda Cups
negative D-score indicates a preference for Panda Cups over Islam

expressions.CDd: positive D-score indicates a preference for Judaism over Panda Cups
negative D-score indicates a preference for Panda Cups over Judaism

Aggregate D-Scores are averaged D-Scores for each offspring group (see guidelines and explanations in Axt et al, 2014).
An aggregate D-score allows the evaluation of each offspring group compared to the others.
Positive scores = more favorable evaluation than the average one across all groups
Negative scores = less favorable evaluation than the average one across all groups

expressions.d_A-
expressions.d_D: aggregate D-scores for the 4 groups
Note: if fewer or more than 4 groups were run with this script,
the calculations for the aggregate scores need to be adjusted
(see section EXPRESSIONS)

values.aggregateCheck: check to ensure that the sum of all 4 aggregates is 0

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

(2) Summary data file: 'religioniat_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)