ArticleStat (International Statistical Institute)2024
What is it that you say you do here? Advocating for the critical role of data scientists in research infrastructure.
Article in Stat (International Statistical Institute), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Clinical and academic research continues to become more complex as our knowledge and technology advance. A substantial and growing number of specialists in biostatistics, data science, and library sciences are needed to support these research systems and promote high-caliber research. However, that support is often marginalized as optional rather than a fundamental component of research infrastructure. By building research infrastructure, an institution harnesses access to tools and support/service centers that host skilled experts who approach research with best practices in mind and domain-specific knowledge at hand. We outline the potential roles of data scientists and statisticians in research infrastructure and recommend guidelines for advocating for the institutional resources needed to support these roles in a sustainable and efficient manner for the long-term success of the institution. We provide these guidelines in terms of resource efficiency, monetary efficiency, and long-term sustainability. We hope this work contributes to-and provides shared language for-a conversation on a broader framework beyond metrics that can be used to advocate for needed resources.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.