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									GNAT Demonstration Program*
SCRIPT INFO

original Script Author: Brian Nosek (nosek@virginia.edu)
Date: 10/29/2000
last updated: 01-12-2016 by K.Borchert (katjab@millisecond.com) for Millisecond Software LLC


BACKGROUND INFO

											*Purpose*
GNAT:  "A test of implicit social cognition with a focus on attitude"

Literature Reference:
Nosek, B. A., & Banaji, M. R. (2001). The go/no-go association task.  Social Cognition, 19(6), 625-666. 


*Note (by B. Nosek - original script author): 
This task is for demonstration purposes only.  Using the GNAT for research 
requires intentional decisions about numerous design parameters.  Discussion of 
some of those parameters can be found in Nosek and Banaji (2001; Social Cognition).
This example is a minimalist example and is not designed to maximize reliability, it
only demonstrates the core properties of the task.


Additional Notes (K. Borchert, Millisecond Software):
GNATdemo.iqx was edited to allow for:
- easy changes in GNAT target categories (under Editable Stimuli)
- easy changes in response timeouts (under Editable Parameters)
	-> by default the task is set up to run 2 different response timeouts (750ms vs. 600ms) for critical testblocks
- easy setting of target vs. noise response timeouts (see Experiment 5 in Nosek & Banaji, 2001)
	-> by default, response timeouts for target and noise trials are the same
- easy changes in interstimulus intervals (time btw. offset of one stimulus and onset of the next) (under Editable Parameters)
- recorded correct responses reflect the actual accuracy of the participant's response while keeping feedback accurate
- includes summary variables (hits and false alarm counts/rates)


											  *Task*
Participants are asked to categorize attributes (e.g. "happy"; "unhappy") and target items (e.g fruits "apple"; insects "bug") 
into predetermined categories via keystroke presses. The basic task is to press the Spacebar if an item (e.g. "happy")
belongs to the category currently being tested (e.g. "Good") and to do nothing if it doesn't.
For practice, participants sort items into categories "Good", "Bad", "Fruit", and "Insect".
For the test, participants are asked to sort categories into the paired/combined categories (e.g. 
"Fruit OR Good"). When an item belongs to either one of these two categories,  participants should press the Spacebar.


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

(1) Raw data file: 'GNATdemo_raw*.iqdat' (a separate file for each participant)

build:							Inquisit build
computer.platform:				the platform the script was run on
date, time, subject, group:		date and time script was run with the current subject/groupnumber 
blocknum/blockcode:				number of the current block and name of current block
trialcode/trialnum:				name and number of current trial
/responsetimeout:				time in ms that is allowed for response in a given trial
/signal:						1 = signal trial (spacebar response is correct); 0 = noisetrial (no response is correct)

/targettype:					"A" vs. "B" (here: A-insects; B-fruit)
/pairing:						"AA" -> targetA-attributeA (here: insects and good)
								"AB" -> targetA-attributeB (here: insects and bad)
								"BA" -> targetB-attributeA (here: fruit-good)
								"BB" -> targetB-attributeB (here: fruit-bad)
/trialtype:						"practice" vs. "test"

stimulusitem:					the presented stimulusitems in order of presentation in stimulusframes (see trials)
response:						response made (either 57 = Spacebar or 0 for no response)
latency:						the latency of the response in ms (or if no response: response timeout duration)
correct:						the accuracy of response (1 = correct; 0 = error)

(2) Summary data file: 'GNATdemo_summary*.iqdat' (a separate file for each participant)

script.startdate:				date script was run
script.starttime:				time script was started
script.subjectid:				subject id number
script.groupid:					group id number
script.elapsedtime:				time it took to run script (in ms)
computer.platform:				the platform the script was run on
/completed:						0 = script was not completed; 1 = script was completed (all condisions run)

/responsetimeout2_signal:		stores the response timeouts in ms used for signals in the first testblock in this script
/responsetimeout2_noise:		stores the response timeouts in ms used for noise in the first testblock in this script
/responsetimeout3_signal:		stores the response timeouts in ms used in this study for signals in the second testblock in this script
/responsetimeout3_noise:		stores the response timeouts in ms used for noise in the second testblock in this script
									Notes: responsetimeouts1 are used for practice only and responsetimeouts4 are not run by default

/propcorrect_AA:				overall proportion correct for pairing targetA-attributeA (here: insects-good); test trials only
/propcorrect_AB:				overall proportion correct for pairing targetA-attributeB (here: insects-bad); test trials only
/propcorrect_BA:				overall proportion correct for pairing targetB-attributeA (here: fruit-good); test trials only
/propcorrect_BB:				overall proportion correct for pairing targetB-attributeB (here: fruit-bad); test trials only

/rHit_AA:						hit rate for pairing targetA-attributeA (here: insects-good) across all responsetimeouts; test trials only
/rFA_AA:						false alarm (FA) rate for pairing targetA-attributeA (here: insects-good) across all responsetimeouts; test trials only
/zhit_AA:						z-score of hit rate for pairings targetA-attributeA (here: insects-good)
/zFA_AA:						z-score of FA rate for pairings targetA-attributeA (here: insects-good)
/AA_dprime:						Computes d' (parametric measure of discriminability) for Insect-Good Pairings
/AA_beta:						Computes ß (beta) (parametric measure of bias) for Insect-Good Pairings

/rHit_AB:						hit rate for pairing targetA-attributeA (here: insects-bad) across all responsetimeouts; test trials only
/rFA_AB:						false alarm (FA) rate for pairing targetA-attributeA (here: insects-bad) across all responsetimeouts; test trials only
/zhit_AB:						z-score of hit rate for pairings targetA-attributeA (here: insects-bad)
/zFA_AB:						z-score of FA rate for pairings targetA-attributeA (here: insects-bad)
/AB_dprime:						Computes d' (parametric measure of discriminability) for Insect-bad Pairings
/AB_beta:						Computes ß (beta) (parametric measure of bias) for Insect-bad Pairings

/rHit_BA:						hit rate for pairing targetA-attributeA (here: Fruits-good) across all responsetimeouts; test trials only
/rFA_BA:						false alarm (FA) rate for pairing targetA-attributeA (here: Fruits-good) across all responsetimeouts; test trials only
/zhit_BA:						z-score of hit rate for pairings targetA-attributeA (here: Fruits-good)
/zFA_BA:						z-score of FA rate for pairings targetA-attributeA (here: Fruits-good)
/BA_dprime:						Computes d' (parametric measure of discriminBAility) for Fruit-good Pairings
/BA_beta:						Computes ß (beta) (parametric measure of bias) for Fruit-good Pairings

/rHit_BB:						hit rate for pairing targetA-attributeA (here: Fruits-bad) across all responsetimeouts; test trials only
/rFA_BB:						false alarm (FA) rate for pairing targetA-attributeA (here: Fruits-bad) across all responsetimeouts; test trials only
/zhit_BB:						z-score of hit rate for pairings targetA-attributeA (here: Fruits-bad)
/zFA_BB:						z-score of FA rate for pairings targetA-attributeA (here: Fruits-bad)
/BB_dprime:						Computes d' (parametric measure of discriminBBility) for Fruit-bad Pairings
/BB_beta:						Computes ß (beta) (parametric measure of bias) for Fruit-bad Pairings

Note: by default, this script runs testblocks for responsetimeouts2 and responsetimeouts3


EXPERIMENTAL SET-UP:

Default GNAT Set-Up in this script:
(1) 4 training blocks: one training block each for targetA (here: insects), targetB (here: fruits), attributeA (here: good), attributeB (here: bad)
with response timeout of 1000ms (editable under section Editable Values)
-> block order is determined randomly
-> run 20 trials each (10 target:10 noise)

(2) 4 test blocks that combine targets and attributes with a faster response timeout (default: 750ms)
-> block order is determined randomly
-> each block runs 16 'practice trials' followed by 60 test trials (summary variables based on test trial performance only)
-> signal : noise = 1 : 1

(3) 4 test blocks that combine targets and attributes with an even faster response timeout (default: 600ms)
-> block order is determined randomly
-> each block runs 16 'practice trials' followed by 60 test trials (summary variables based on test trial performance only)
-> signal : noise = 1 : 1

Notes: 
* Number of trials run as well as 'signal : noise' ratios can only be edited on block level (see section BLOCKS)

STIMULI
see section Editable Stimuli

INSTRUCTIONS
see section Editable Instructions

EDITABLE CODE:
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:

/responsetimeout1_signal:						stores the longest response timeouts in ms used in this study for targets
													Note: by default, the longest response timeout in this script is used for blocks
													that test attributes and targets separately (default: 1000ms)
/responsetimeout2_signal:						stores the next response timeouts in ms used in this study for targets
													Note: by default, in this script this is the first response time used for blocks
													that test attributes and targets simultaneously (default 750ms)
/responsetimeout3_signal:						stores the next response timeouts in ms used in this study for targets
													Note: by default, this is the second response time used for blocks
													that test attributes and targets simultaneously (default 600ms)
/responsetimeout4_signal:						stores a potential next response timeouts in ms that could be used for targets
												-> code provided under section BLOCKS
													Note: by default, this responsetimeout4_signal is not used in this script

(same for noise trials: by default they are the same in this script)

												!!!NOTE: "The most effective response deadlines for measuring automatic cognition are those fast enough
												to eliminate perfect responding but not so fast as to lower accuracy substantially, with an 
												approporiate range of response deadlines falling between 500 and 850ms." (Nosek & Banaji, 2001, p.636)

/isi:											stores the interstimulus interval (time between offset of one stimulus and onset of next)
											


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