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Ulferts, Gregory W.; Cannon, Nicholas J.; Howard, Terry L. – Research in Higher Education Journal, 2021
This research seeks to describe the continuing predicament of R&D funding in the U.S. and to provide support for a return to higher R&D spending as a proportion of GDP to maintain American leadership in innovation. Historically, government investment has funded most foundational scientific research leading to technological advances in…
Descriptors: Research and Development, Financial Support, Scientific Research, Federal Aid
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Coyle, Caitlin E.; Schulman-Green, Dena; Feder, Shelli; Toraman, Sinem; Prust, Margaret L.; Plano Clark, Vicki L.; Curry, Leslie – Journal of Mixed Methods Research, 2018
Although investigators in health sciences are increasingly interested in using mixed methods, greater adoption requires funding opportunities. Funding allocations can signal recognition of a particular methodology and proficiency of investigators in using such methods. We examined trends in prevalence of mixed methods research funded by federal…
Descriptors: Federal Aid, Mixed Methods Research, Health Sciences, Trend Analysis
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Fanshawe, Thomas R.; Shaw, Luke F.; Spence, Graeme T. – Research Synthesis Methods, 2017
Introduction: Previous studies suggest that many systematic reviews contain meta-analyses that display temporal trends, such as the first study's result being more extreme than later studies' or a drift in the pooled estimate. We assessed the extent and characteristics of temporal trends using all Cochrane intervention reports published 2008-2012.…
Descriptors: Meta Analysis, Intervention, Databases, Medical Research
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Dogo, Samson Henry; Clark, Allan; Kulinskaya, Elena – Research Synthesis Methods, 2017
Temporal changes in magnitude of effect sizes reported in many areas of research are a threat to the credibility of the results and conclusions of meta-analysis. Numerous sequential methods for meta-analysis have been proposed to detect changes and monitor trends in effect sizes so that meta-analysis can be updated when necessary and interpreted…
Descriptors: Effect Size, Meta Analysis, Visualization, Error of Measurement