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- Schweinsberg, Martin, et al.
(författare)
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Same data, different conclusions : Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis
- 2021
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Ingår i: Organizational Behavior and Human Decision Processes. - : Elsevier BV. - 0749-5978 .- 1095-9920. ; 165, s. 228-249
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Tidskriftsartikel (refereegranskat)abstract
- 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 orga-nizations and leaders, whose decision making relies in part on scientific findings, consulting reports, and internal analyses by data scientists, are discussed.
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| 2. |
- Rohr, Julia K., et al.
(författare)
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HIV treatment cascade for older adults in rural South Africa
- 2020
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Ingår i: Sexually Transmitted Infections. - : BMJ Publishing Group Ltd. - 1368-4973 .- 1472-3263. ; 96:4, s. 271-276
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: The HIV treatment cascade is a powerful framework for understanding progress from initial diagnosis to successful treatment. Data sources for cascades vary and often are based on clinical cohorts, population cohorts linked to clinics, or self-reported information. We use both biomarkers and self-reported data from a large population-based cohort of older South Africans to establish the first HIV cascade for this growing segment of the HIV-positive population and compare results using the different data sources.Methods: Data came from the Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community in South Africa (HAALSI) 2015 baseline survey of 5059 adults aged 40+ years. Dried blood spots (DBS) were screened for HIV, antiretroviral drugs and viral load. In-home surveys asked about HIV testing, diagnosis and antiretroviral therapy (ART) use. We calculated proportions and CIs for each stage of the cascade, conditional on attainment of the previous stage, using (1) biomarkers, (2) self-report and (3) both biomarkers and self-report, and compared with UNAIDS 90-90-90 targets.Results: 4560 participants had DBS results, among whom 1048 (23%) screened HIV-positive and comprised the denominator for each cascade. The biomarker cascade showed 63% (95% CI 60 to 66) on ART and 72% (95% CI 69 to 76) of those on ART with viral suppression. Self-reports underestimated testing, diagnosis and ART, with only 47% (95% CI 44 to 50) of HIV-positive individuals reporting ART use. The combined cascade indicated high HIV testing (89% (95% CI 87 to 91)), but lower knowledge of HIV-positive status (71% (95% CI 68 to 74)).Conclusions: Older South Africans need repeated HIV testing and sustained ART to reach 90-90-90 targets. HIV cascades relying on self-reports are likely to underestimate true cascade attainment, and biomarkers provide substantial improvements to cascade estimates.
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