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Predictive Models For Time To Acceptance: An Example Using “Hurricane” Articles in AMS Journals

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  • 1 Florida State University, Tallahassee, Florida
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The authors demonstrate a statistical model for the time it takes a manuscript to be accepted for publication. The manuscript received and accepted dates from published manuscripts with the term “hurricane” in the title are obtained from the American Meteorological Society's online publication search feature. The time to acceptance as the difference in days between these two dates is modeled using a Bayesian approach. Assuming an article picked at random gets published, draws from the posterior distribution of the modeled time-to-acceptance parameter indicate about a 12% chance that it will spend more than 210 days (7 months) in review. The model can be adapted to fit similar data obtained using other search criteria.

CORRESPONDING AUTHOR: Robert E. Hodges, Department of Geography, Florida State University, Tallahassee, FL 32306, E-mail: reh3682@fsu.edu

The authors demonstrate a statistical model for the time it takes a manuscript to be accepted for publication. The manuscript received and accepted dates from published manuscripts with the term “hurricane” in the title are obtained from the American Meteorological Society's online publication search feature. The time to acceptance as the difference in days between these two dates is modeled using a Bayesian approach. Assuming an article picked at random gets published, draws from the posterior distribution of the modeled time-to-acceptance parameter indicate about a 12% chance that it will spend more than 210 days (7 months) in review. The model can be adapted to fit similar data obtained using other search criteria.

CORRESPONDING AUTHOR: Robert E. Hodges, Department of Geography, Florida State University, Tallahassee, FL 32306, E-mail: reh3682@fsu.edu
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