'Sequential collaboration long chains' (AsPredicted #98,213)
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 2022/05/26 02:14 (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: Change probability decreases over the course of a sequential chain.
Hypothesis 2: Accuracy of judgments increase over the course of a sequential chain.
Hypothesis 3: Estimates obtained with sequential collaboration are more accurate for shorter sequential chains than unweighted averaging for smaller groups of participants, while unweighted averaging yields more accurate estimates for larger groups of participants compared to longer sequential chains.
Exploratory analysis:
Investigate how judgments that are already correct in the beginning of a sequential chain develop over the course of a sequential chain. Expectation: Judgments will be adjusted and thus worsened by participants in the sequential chain and reach the same average accuracy as all judgments in the sequential chain.
3) Describe the key dependent variable(s) specifying how they will be measured. Change probability: Probability that participants adjust a presented jugment in a sequential chain
Judgment accuracy: Euclidean distance between a judgment and the correct location of the city
Estimate accuracy: Euclidean distance between the aggregate over several judgments (either unweighted averaged or developed within a sequential chain) and the correct location of the city
4) How many and which conditions will participants be assigned to? Questionnaires:
- independent-judgments questionnaire: Participants are presented with 62 European cities which they should locate on respective maps
- sequential-collaboration questionnaire: Participants are presented with the judgment of a previous participant for 62 European cities and can decide to either adjust or maintain the presented judgment
Conditions:
- sequential collaboration: Sequential chains of 25 participants are built with one participant completing the independent-judgments questionnaire starting the sequential chain and 24 participants completing the sequential-collaboration questionnaire following
- unweighted averaging: Judgments of groups of 25 participants are averaged to obtain estimates with unweighted averaging
Additional manipulation:
- six judgments of participants completing the independent-judgments questionnaire are randomly selected and replaced with the correct location of a city to allow an investigation of the exploratory analysis
5) Specify exactly which analyses you will conduct to examine the main question/hypothesis. We analyze all hypotheses using linear mixed models to account for the nested structure of our data.
Thereby, sequential chains that started with correct locations which replaced original judgments are excluded from the analysis and are only considered in the exploratory analysis.
6) Describe exactly how outliers will be defined and handled, and your precise rule(s) for excluding observations. Participants will be excluded if they position the majority of their judgments outside the highlighted coutries, if they show answer patterns that hint towards looking up answers, and if they position their judgments mostly at the same position hinting towards just clicking through the study.
Furthermore, we exclude single judgments and respective sequential chains for judgments if they were timed out after 40 seconds.
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 plan to collect data of 700 participants, of which 500 will be assigned to sequential chains and 200 will be assigned to provide independent individual judgments.
8) Anything else you would like to pre-register? (e.g., secondary analyses, variables collected for exploratory purposes, unusual analyses planned?) A soft launch with 10% of the sample was already started but this data has not been analyzed.
