Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
MetadataShow full item record
In this crowdsourced initiative, independent analysts used the same dataset to test two hypotheses regarding the effects of scientists’ gender and professional status on verbosity during group meetings. Not only the analytic approach but also the operationalizations of key variables were left unconstrained and up to individual analysts. For instance, analysts could choose to operationalize status as job title, institutional ranking, citation counts, or some combination. To maximize transparency regarding the process by which analytic choices are made, the analysts used a platform we developed called DataExplained to justify both preferred and rejected analytic paths in real time. Analyses lacking sufficient detail, reproducible code, or with statistical errors were excluded, resulting in 29 analyses in the final sample. Researchers reported radically different analyses and dispersed empirical outcomes, in a number of cases obtaining significant effects in opposite directions for the same research question. A Boba multiverse analysis demonstrates that decisions about how to operationalize variables explain variability in outcomes above and beyond statistical choices (e.g., covariates). Subjective researcher decisions play a critical role in driving the reported empirical results, underscoring the need for open data, systematic robustness checks, and transparency regarding both analytic paths taken and not taken. Implications for organizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
Showing items related by title, author, creator and subject.
Phatak, Aloke (2018)The recent initiative by the Actuaries Institute to incorporate a data science/analytics unit at the Honours or Masters level, as well as the changes to the undergraduate curriculum that will start in 2020, means that ...
Berwick, Lyndon (2009)The analytical capacity of MSSV pyrolysis has been used to extend the structural characterisation of aquatic natural organic matter (NOM). NOM can contribute to various potable water issues and is present in high ...
Towards a global participatory platform: Democratising open data, complexity science and collective intelligenceBuckingham Shum, S.; Aberer, K.; Schmidt, A.; Bishop, S.; Lukowicz, P.; Anderson, S.; Charalabidis, Y.; Domingue, J.; de Freitas, Sara; Dunwell, I.; Edmonds, B.; Grey, F.; Haklay, M.; Jelasity, M.; Karpistsenko, A.; Kohlhammer, J.; Lewis, J.; Pitt, J.; Sumner, R.; Helbing, D. (2012)The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools ...