Crowdsourcing hypothesis tests: Making transparent how design choices shape research results

To what extent are the results of research investigations influenced by subjective decisions that scientists make as they design studies? Fifteen research teams independently designed studies to answer five original research questions related to moral judgments, negotiations, and implicit cognition. Participants from two separate, large samples (total N > 15,000) were then randomly assigned to complete one version of each study. Effect sizes varied dramatically across different sets of materials designed to test the same hypothesis: materials from different teams rendered significant effects in opposite directions for four out of five hypotheses, with the narrowest range in estimates being d = -0.37 to 0.26. Meta-analysis indicated a lack of overall support for two original hypotheses, mixed support for one hypothesis, and significant support for two hypotheses. Overall, none of the variability in effect sizes was attributable to the skill of the research team in designing materials, while some variability was attributable to the hypothesis being tested. In a forecasting survey, predictions of other scientists were strongly correlated with study results, and average predictions were similar to observed outcomes. Crowdsourced testing of research hypotheses helps reveal the true consistency of empirical support for a scientific claim.