Strategy vs. Direct Response Method

Last registered on September 20, 2019
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Pre-Trial

Trial Information

General Information

Title
Strategy vs. Direct Response Method
RCT ID
AEARCTR-0004737
Initial registration date
September 20, 2019

Initial registration date is when the trial was registered.

It corresponds to when the registration was submitted to the Registry to be reviewed for publication.

First published
September 20, 2019, 9:44 AM EDT

First published corresponds to when the trial was first made public on the Registry after being reviewed.

Locations

Country
United States of America
Region

Primary Investigator

Name
Marcus Roel
Affiliation
Beijing Normal University
Contact Primary Investigator

Other Primary Investigator(s)

PI Name
Zhuoqiong Chen
PI Affiliation
Harbin Institute of Technology, Shenzhen
Contact Investigator

Additional Trial Information

Status
In development
Start date
2019-10-07
End date
2020-10-06
Keywords
Other
Additional Keywords
Strategy Method, Direct Response Method, Beliefs
JEL code(s)
C72, C90, C91, C92, D63
Secondary IDs
Shenzhen Peacock Plan
Abstract
This document outlines a plan for an experiment that investigates when behavior in experiments that employ the strategy method coincides with or differs from experiments that use the direct response method.
External Link(s)

Registration Citation

Citation
Chen, Zhuoqiong and Marcus Roel. 2019. "Strategy vs. Direct Response Method." AEA RCT Registry. September 20. https://doi.org/10.1257/rct.4737-1.0
Sponsors & Partners
Experimental Details

Interventions

Intervention(s)
n/a
Intervention Start Date
2019-10-07
Intervention End Date
2020-10-06

Primary Outcomes

Primary Outcomes (end points)
Player 1 and Player 2 choices.
Primary Outcomes (explanation)
n/a

Secondary Outcomes

Secondary Outcomes (end points)
Player beliefs; Control questions with regards to experimental instructions; survey questions such as gender, age, location, field of study, type of degree, employment status, household income, and previous experience with experiments
Secondary Outcomes (explanation)
n/a

Experimental Design

Experimental Design
n/a
Experimental Design Details
Experimental setting:

The experiment is run on Amazon Turk with participant’s locations restricted to the USA.
Subjects play both games in random order and are randomly assigned to the role of player 1 or player 2 for the entire experiment. Subjects interact with a different participant for the second game.

If we assume that the dif-in-dif effect of beliefs is 10%, a power analysis suggests that we require around* 550 subjects at a given node to detect such difference in player 2’s behavior. (* the exact number varies slightly with the levels of player 2’s selfish/non-selfish behavior). As we only observe one response of player 2 under the direct response method, we increase the sample of the direct response treatment.

Overall, we plan to obtain 500 observations for each of the strategy method treatments and 1500 observations for each of the direct response method treatments. We triple observations for the direct response method as player 1 is unlikely to take each of his action with equal probability. For reasonable frequencies of selfish to non-selfish behavior by both player 1 and player 2, this results in a power of 80% at a 10% significance level.

Caveat: Since the order of games is random, this analysis assumes that there is no order effect present in the data. If we were to detect an order effect, we would double the observations in order to obtain the same power.
Randomization Method
randomization is automatically done by a computer at the time the individual starts the experiment
Randomization Unit
the unit (clusters) of randomization in our experiment is at the individual level
Was the treatment clustered?
No

Experiment Characteristics

Sample size: planned number of clusters
equals the total number of participants
Sample size: planned number of observations
4000 people
Sample size (or number of clusters) by treatment arms
500 for each of the two strategy method treatments, 1500 for each of the two direct response method treatments
Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
At a power of 80% and a significance level of 10%, the minimum detectable effect size is a difference of 10 percentage points.
Supporting Documents and Materials
IRB

Institutional Review Boards (IRBs)

IRB Name
IRB Approval Date
IRB Approval Number
Analysis Plan

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Post-Trial

Post Trial Information

Study Withdrawal

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Intervention

Is the intervention completed?
No
Data Collection Complete
Data Publication

Data Publication

Is public data available?
No

Program Files

Program Files
Reports, Papers & Other Materials

Relevant Paper(s)

Reports & Other Materials