Author(s) Maren Mayer (University of Mannheim) - maren.mayer@iwm-tuebingen.de Daniel W. Heck (Philipps-Universität Marburg) - daniel.heck@uni-marburg.de
Pre-registered on 2020/11/20 01:35 (PT)
1) Have any data been collected for this study already? It's complicated. We have already collected some data but explain in Question 8 why readers may consider this a valid pre-registration nevertheless.
2) What's the main question being asked or hypothesis being tested in this study? Hypothesis 1: Judgments of participants become more accurate over a sequential chain.
Hypothesis 2: The final estimate of a sequential chain is more accurate than that of wisdom of crowds.
3) Describe the key dependent variable(s) specifying how they will be measured. Participants have to locate 57 cities on geographical maps and we will analyze the x- and y-coordinates of these judgments. We analyze judgments as euklidean distance from the correct position and as two-dimensional models.
For Hypothesis 1, the dependent variable is the individual judgment over a sequence in the sequential collaboration condition.
For Hypothesis 2, we compare the wisdom of crowds estimate (mean of all judgments of a group in the wisdom of crowds condition) with the sequential collaboration estimate (final judgment of a group in the sequential collaboration condition).
4) How many and which conditions will participants be assigned to? Between-subjects-design with two conditions:
- wisdom of crowds: participants in this condition have to locate 57 cities on geographical maps
- sequential collaboration: participants in this condition see the previous judgments of other participants regarding the location of 57 cities and have the opportunity to correct the location
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. Hypothesis 1: We compare the judgments for each sequence step (4 steps) with a linear mixed model (judgment ~ sequence + (sequence | item) ).
Hypothesis 2: We compare the estimates of wisdom of crowds and sequential collaboration with a linear mixed model (estimate ~ condition + (condition | item) ).
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. We will exclude participants with irregular answer patterns (e.g. clicking the same spot on the screen repeatedly or clicking outside the highlighted countries) for more than 10% of the items.
Furthermore, we will exclude judgments that were timed out (participants will need to answer within 30 seconds) and judgments that are located 1.5 interquartile ratio from the 1st and 3rd quartile.
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. We recruit 400 participants over a German online panel provider.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) Data collection started today with a soft launch of only 10% of the full sample size. We have not analyzed any data and will not until the full sample size of 400 participants is reached.
