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- W2023472247 abstract "Dissemination of ideas from theory to practice is a significant challenge in statistics. Quick identification of articles useful to practitioners would greatly assist in this dissemination, thereby improving science. This article uses the citation count history of articles to identify key papers from 1985 to 2002 from 12 statistics journals for applied biostatisticians. One feature requiring attention in order to appropriately rank an article’s impact is assessment of the citation accrual patterns over time. Citation counts in statistics differ dramatically from fields such as medicine. In statistics, most articles receive few citations, with 15-year-old articles from five key journals receiving a median of 13 citations compared to 66 in the Journal of Clinical Oncology. However, statistics articles in the top 2%–3% continue to gain citations at a high rate past 15 years, exceeding those in JCO, whose counts slow dramatically around 8 years past publication. Articles with the highest expected applied uses 20 years post publication were identified using joinpoint regression. In this evaluation, the fraction of citations that represent applied use was defined and estimated. The false discovery rate, quantification of heterogeneity in meta-analysis, and generalized estimating equations rank as the ideas with the greatest estimated applied impact." @default.
- W2023472247 created "2016-06-24" @default.
- W2023472247 creator A5061312918 @default.
- W2023472247 date "2010-11-01" @default.
- W2023472247 modified "2023-10-18" @default.
- W2023472247 title "Identifying Key Statistical Papers From 1985 to 2002 Using Citation Data for Applied Biostatisticians" @default.
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- W2023472247 doi "https://doi.org/10.1198/tast.2010.08250" @default.
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