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A clear approach to conducting higher education policy analysis | Numerous examples, exercises, and data sets in policy analysis | Learn Stata - sample syntax written in Stata | Sample PowerPoint presentations explaining education policy analysis
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Autorenporträt
Dr. Marvin A. Titus' research focuses on the economics and finance of higher education and quantitative methods. While he has explored how institutional and state finance influence student retention and graduation, Dr. Titus' most recent work is centered on examining the determinants of institutional cost and productivity efficiency. He investigates how state higher education finance policies influence degree production. Through the use of a variety of econometric techniques, Dr. Titus is also exploring how state business cycles influence volatility in state funding of higher education. Named a TIAA Institute Fellow in 2018, Dr. Titus has published in top-tier research journals, including in the Journal of Higher Education, Research in Higher Education and Review of Higher Education. He is an associate editor of Higher Education: Handbook of Theory and Research, and has served on the editorial board of Research in Higher Education, Review ofHigher Education and the Journal of Education Finance. Dr. Titus also serves on several technical review panels for national surveys produced by the National Center for Education Statistics. To conduct his research utilizing national and customized state and institution-level datasets, Dr. Titus uses several statistical software packages such as Stata, Limdep, and HLM. He earned a BA in economics and history from York College of the City University of New York, an MA in economics from the University of Wisconsin-Milwaukee, and a PhD in higher education policy, planning, and administration from the University of Maryland.
Inhaltsangabe
1. Introduction.- 2. Asking and answering policy questions.- 3. Identifying data sources and creating custom datasets.- 4. Managing data.- 5. Getting to know "thy" data.- 6. Using descriptive statistics and graphs.- 7. Introducing intermediate statistical methods.- 8. Introducing advanced statistical methods.- 9. Presenting the analysis to higher education policy makers.- 10. Conclusion.
