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Multiple Identities and Attentiveness
Last registered on May 18, 2021

Pre-Trial

Trial Information
General Information
Title
Multiple Identities and Attentiveness
RCT ID
AEARCTR-0007623
Initial registration date
May 17, 2021
Last updated
May 18, 2021 9:42 AM EDT
Location(s)

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Primary Investigator
Affiliation
University of Warwick
Other Primary Investigator(s)
PI Affiliation
University of Warwick
PI Affiliation
Nanyang Technological University
Additional Trial Information
Status
In development
Start date
2021-05-21
End date
2021-12-31
Secondary IDs
Abstract
We all have many identities whether it be our gender, age/cohort, class, political affiliation, race, religion or dietary preferences. There is a large literature on the role of identity in decision-making but most of them focus on scenarios where identity is uni-dimensional. In this study, we focus instead on scenarios where identity may be multi-dimensional. In particular, we seek to examine how the number of salient dimensions of identity may cause shifts in the strength of identities and hence behavior.
External Link(s)
Registration Citation
Citation
Sgroi, Daniel, Jonathan Yeo and SHI ZHUO. 2021. "Multiple Identities and Attentiveness." AEA RCT Registry. May 18. https://doi.org/10.1257/rct.7623-1.0.
Experimental Details
Interventions
Intervention(s)
This is a two-arm between subject design. We vary whether there is 1) one dimension of identity or 2) two dimensions of identity made salient to subjects. When there is only one salient dimension of identity, we will randomly assign them one of the two available dimensions. Subjects then have to allocate some credits (i.e., experimental currency) between 2 random participants given information on their identities. More detail is provided in the attached Analysis Plan.
Intervention Start Date
2021-05-21
Intervention End Date
2021-08-30
Primary Outcomes
Primary Outcomes (end points)
Identity strength on each dimension as measured by their decisions in the third-party allocation task
Primary Outcomes (explanation)
The effective allocation to a participant with same identity when the two random participants have opposite identities in the dimension.
(If they choose to implement their raw allocation decision, the effective allocation is just their "raw" allocation, otherwise, it will be a 50-50 allocation which is the (expected) allocation when choosing to split randomly or equally).
Secondary Outcomes
Secondary Outcomes (end points)
We have 2 secondary-measures which are sub-components of our main measure. 1)The raw allocation to a participant with the same identity when the two random participants have opposite identities in the dimension. 2) Whether participants choose to implement their raw allocation decisions, or decide to always split randomly or equally between the two random participants.
Beliefs of the distribution of identities on the two dimensions elicited in an incentivized way in the questionnaire
Secondary Outcomes (explanation)
In the questionnaire after the allocation task, each participant has to answer a question of 4 different beliefs. Their answers are incentivized to be accurate. The 4 beliefs are as follows:
1) Among all participants who belong to the group that agrees with the statement on religion, what is the percentage that belong to the group that agrees with the statement on government;
2) Among all participants who belong to the group that disagrees with the statement on religion, what is the percentage that belong to the group that agrees with the statement on government;
3) Among all participants, what is the percentage that belong to the group that agrees with the statement on religion;
4) Among all participants, what is the percentage that belong to the group that agrees with the statement on government. One of the four questions is randomly selected for payment. If the selected answer is within 2% of the true value, the participant will get a bonus (with a higher bonus if the answer is within 1% or exactly correct).
Experimental Design
Experimental Design
This study uses an online experiment to examine the effect of the number of dimensions of salient identity on identity strength and ingroup biases in each dimension. At the beginning of the experiment, participants will have particular identities made salient to them. They subsequently play an incentivized third-party allocation task which is used to elicit strength of their identities. At the end of the experiment, there is a post-experiment questionnaire, which includes an incentivized elicitation of their beliefs of the distribution of identities on both dimensions. More detail is provided in the attached Analysis Plan.
Experimental Design Details
Not available
Randomization Method
Randomization done by the experiment program when a session begins.
Stratified sampling is used to reduce sampling error.
There are six strata given by a participant's political affiliation and religion affiliation: Demographic/Republican/Independent X Religious/Non-religious. The information is given by the demographic screener on Prolific.
Simple random sampling is applied within each stratum: half of the participants in each stratum will be randomly assigned to the 1 dimension treatment, while the other half will be assigned to the 2 dimension treatment.
Randomization Unit
Randomization unit is at the individual level.
Was the treatment clustered?
No
Experiment Characteristics
Sample size: planned number of clusters
480-750 participants
Sample size: planned number of observations
480-750 participants
Sample size (or number of clusters) by treatment arms
240-375 participants in control group with one salient dimension of identity (one of the two dimensions randomly selected)
240-375 participants in treatment group with two salient dimensions of identity (randomise the order of the two dimensions)
80-125 participants in each stratum
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The software Optimal Design (Raudenbush et al., 2011) is used for power calculation. We only have one key hypothesis so no adjustment for multiple hypotheses testing is needed. A fixed-effect blocked trial model is used. In the pilot, we found the two stratification variables explained around 8.17% of the variance for the main outcome variable. Using this number, power = 0.8, alpha = 0.05, with equal SD and six strata, a sample size N=480 (80 in each stratum) is associated with a MDE of 0.247. In Chen and Li (2009), chatting with one’s ingroup results in an increase in ingroup bias with effect sizes ranging from 0.08 to 0.29 SD. If we take an intermediate value of around 0.2 SD as an estimate for our effect size, we will need a sample size of N=750 (125 in each stratum).Since we do not know the exact effect size and underlying variation, we will first target a sample size of 480. After gaining a better idea of the variance of the underlying population, we will potentially follow up with a larger sample size if needed.
IRB
INSTITUTIONAL REVIEW BOARDS (IRBs)
IRB Name
Humanities and Social Sciences Research Ethics Committee
IRB Approval Date
2020-06-09
IRB Approval Number
HSSREC 178/19-20
Analysis Plan

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