State investments in psychiatric innovation: investigating unmeasured state factors
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- 作者：Marisa Elena Domino (1) (2)
Christopher Alan Beadles (1) (3) - 关键词：Panel data ; Fixed effects ; Random effects ; Innovation ; State factors
- 刊名：Health Services and Outcomes Research Methodology
- 出版年：2014
- 出版时间：June 2014
- 年：2014
- 卷：14
- 期：1-2
- 页码：34-53
- 全文大小：
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Christopher Alan Beadles (1) (3)
1. Department of Health Policy and Management, The Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 1104G McGavran-Greenberg Hall, 135 Dauer Dr, Chapel Hill, NC, 27599-7411, USA
2. Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599-7411, USA
3. Center for Health Services Research in Primary Care, Department of Veterans Affairs, Durham VA Medical Center, 508 Fulton Street, Durham, NC, 27713, USA - ISSN：1572-9400
文摘
We apply three separate panel data estimation methods to examine the diffusion of technologies at the state-level. These methods include the Hausman–Taylor random effects model, the fixed effects vector decomposition, and generalized estimating equations. We discuss the assumptions required of each and assess the stability of our policy results across the three models for a longitudinal study of the diffusion of newer psychotropic technologies. We find a reasonable level of consistency among marginal effects for time varying independent variables between our three estimation methods but some discrepancy in the estimated measure of precision in our empirical application. We find a number of policy conclusions are quite stable across estimation methods and may be of interest to state-level mental health policy decision makers.