'Social Learning, Behavioral Biases and Group Outcomes' (AsPredicted #130499)
Author(s) Andrea Amelio (University of Bonn) - aamelio@uni-bonn.de
Pre-registered on 04/28/2023 12:38 AM (PT)
1) Have any data been collected for this study already? No, no data have been collected for this study yet.
2) What's the main question being asked or hypothesis being tested in this study? Does social learning reduce or amplify errors induced by well-established cognitive biases? Does this vary depending on the type of bias? Does the within-task correlation between relative confidence and relative performance predict this?
3) Describe the key dependent variable(s) specifying how they will be measured. - Net gain from social learning: the net gain from social learning is constructed as follows. First, it considers the number of "optimal switchers": participants who switched from a wrong to a correct answer. Second, it considers the "overlearners": participants who switched from a correct answer to a wrong one. The net gain from social learning is the weighted sum of "optimal switchers" and "overlearners", with the weights being the pre-learning optimality rates and its complement over 1, respectively.
-Within task relative confidence-relative performance correlation: Pearson's correlation coefficient between relative confidence and relative performance measures. Relative confidence is constructed as a difference between participants' reported confidence in their action and their assessment of the optimality probability of the observed action. Relative performance is a dummy variable, equal to 1 if the participants' answer is better than the observed answer, and 0 otherwise.
Additionally, I will also look into the switching rates by task and at relative confidence levels by task.
4) How many and which conditions will participants be assigned to? Participants face 10 different cognitive tasks in random order. For each task, there are two phases. First, participants solve the task, choosing an answer. Second, they are shown an action from another participant and may change their initial choice. Participants are asked about both their confidence in their initial choice and their guess of the probability of the observed action being optimal. For each task, participants are shown the optimal action if their initial answer is wrong and, vice versa, a wrong action if their initial answer is correct.
Two conditions:
Baseline: participants provide a guess of the observed action optimality probability.
OtherConfidence: participants are shown the level of confidence reported by the other participant.
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. Three main analyses:
1) Examine how the average net gain from social learning varies between tasks (testing whether it is significantly different from 0 for each task).
2) Examine how relative confidence-relative performance correlation sign and magnitude relate to the net gain from social learning.
3) Examine how relative confidence relates to switching behavior. Specifically, both for the whole sample and for each task, test if relative confidence differs for switchers and non-switchers. Additionally, run a probit regression of relative confidence on the probability of switching, controlling for demographic characteristics.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Participants who fail a comprehension question are excluded from the study and therefore do not count towards the number of completes.
7) How many observations will be collected or what will determine sample size? No need to justify decision, but be precise about exactly how the number will be determined. Baseline: 300 participants
OtherConfidence: 200 participants
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) Additional demographics:
- Sex at birth
- Age
- Education level
I also plan to run the main analyses separately by demographics. In particular, I plan to examine how net gain from social learning and relative confidence-relative performance correlation change for different demographic groups.