___________________________________________________________________________________________________________________ Partner GNAT Script ___________________________________________________________________________________________________________________ last updated: 02-23-2022 by K. Borchert (katjab@millisecond.com) for Millisecond Software, LLC Script Copyright © 02-23-2022 Millisecond Software ___________________________________________________________________________________________________________________ BACKGROUND INFO ___________________________________________________________________________________________________________________ This script implements a partner Go-Nogo Association Task (GNAT) using the category 'partner' as the target category. In general, the GNAT procedure uses the Go-Nogo framework of responding to signal and noise stimuli to investigate implicit bias towards a target category. In contrast to reaction time based tests of implicit bias (e.g. Implicit Association Test), the GNAT framework mainly focuses on accuracy data and specifically d prime measures (measures of sensitivity to distinguish signals from noise in signal detection theory) to infer implicit bias. For example, a positive association of 'partner' (the target signal) is suggested if the dprime measure in the condition 'Partner-Good' (aka both 'partner' and good attributes are signals) is greater than the dprime measure in the condition 'Partner-Bad' (aka both 'partner' and bad attributes are signals). This script implements the Partner GNAT procedure (study 2) described in: Lee, S., Rogge, R. D., & Reis, H. T. (2010). Assessing the seeds of relationship decay: Using implicit evaluations to detect the early stages of disillusionment. Psychological Science, 21(6), 857-864. This script calculates d'prime values. Adjustments to z-scores as described by: Gregg, A. & Sedikides, C. (2010). Narcissistic Fragility: Rethinking Its Links to Explicit and Implicit Self-esteem, Self and Identity, 9:2, 142-161 (p.148) ___________________________________________________________________________________________________________________ TASK DESCRIPTION ___________________________________________________________________________________________________________________ Participants are asked to categorize attributes and partner-related items (e.g words "supportive", "partner name") into predetermined categories via keystroke presses. The basic task is to press the Spacebar if an item (e.g. supportive") belongs to the category currently being tested (e.g. "Constructive"") and to do nothing if it doesn't. For practice, participants sort items into categories "Constructive", and "Destructive". For the test, participants are asked to sort categories into the paired/combined categories (e.g. "Partner OR Constructive"). When an item belongs to either one of these two categories, participants should press the Spacebar. ___________________________________________________________________________________________________________________ DURATION ___________________________________________________________________________________________________________________ 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: 'partnergnat_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 session: 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. stimulusitem: the presented stimuli in order of trial presentation response: the participant's response (scancode of response buttons) correct: accuracy of response: 1 = correct response; 0 = otherwise latency: the response latency (in ms); measured from: onset of stimuli (2) Summary data file: 'partnergnat_summary*.iqdat' (a separate file for each participant) inquisit.version: Inquisit version run computer.platform: the platform the script was run on (win/mac/ios/android) startDate: date script was run startTime: time script was started subjectid: assigned subject id number groupid: assigned group id number sessionid: assigned session id number elapsedTime: time it took to run script (in ms); measured from onset to offset of script completed: 0 = script was not completed (prematurely aborted); 1 = script was completed (all conditions run) Note: z-score calculations: adjustments (see Gregg & Sedikides, 2010, p.148) If the hit rate FA rate is 0 => 0.005 is used instead (aka 0.005 is added to the hitFA rate) IF the hit rate FA rate is 1.0 => 0.995 is used instead (aka 0.005 is subtracted from the hitFA rate) pg_hits: number of Hits for the partner/good pairing pg_falsealarms: number of false alarms for the partner/good pairing pb_hits: number of Hits for the partner/bad pairing pb_falsealarms: number of false alarms for the partner/bad pairing pg_hr: hitrate for partner/good pairing pg_fr: false alarm rate for partner/good pairing pg_z_hr: z-value of hitrate for partner/good pairing pg_z_fr: z-value of false alarm rate for partner/good pairing pg_dprime: d' for partner/good pairing => Range (in this script): -5.1516586840152740479 <= dprime <= 5.1516586840152740479 (=perfect performance) pb_hr: hitrate for partner/bad pairing pb_fr: false alarm rate for partner/bad pairing pb_z_hr: z-value of hitrate for partner/bad pairing pb z-fr: z-value of false alarm rate for partner/bad pairing pb_dprime: d' for partner/bad pairing => Range (in this script): -5.1516586840152740479 <= dprime <= 5.1516586840152740479 (=perfect performance) dprime_Diff: the difference in dprime btw. 'partner-good' and 'partner-bad' => if d prime for 'partner-good' is larger than for 'partner-bad' (positive difference): participant more closely associated Partner with Good than with Bad attributes => if d prime for 'partner-good' is smaller than for 'partner-bad' (negative difference): participant more closely associated Partner with Bad than with Good attributes ___________________________________________________________________________________________________________________ EXPERIMENTAL SET-UP ___________________________________________________________________________________________________________________ * 2 Practice Blocks of 16 trials (8 go/8 nogo): good -> bad -> items are randomly sampled * 2 test blocks (order counterbalanced by groupnumber): -> testing of paired categories "partner OR good" vs. "partner OR bad" -> items are randomly sampled -> 70 trials: 20 partner (go trials), 20 attribute go trials, 30 attribute no-go trials ___________________________________________________________________________________________________________________ STIMULI ___________________________________________________________________________________________________________________ can be edited under section Editable Stimuli ___________________________________________________________________________________________________________________ INSTRUCTIONS ___________________________________________________________________________________________________________________ can be edited under 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: intertrialinterval default is 400ms responsetimeout default is 600ms