1,720,973 research outputs found
Modeling the Incidence and Timing of Student Attrition: A Survival Analysis Approach to Retention Analysis
No full textPresented at the National Symposium on Student Retention, Kansas City, MO, June 2-6, 2007. The Symposium was sponsored by the Consortium for Student Data Exchange (CSRDE).Radcliffe, Peter M.; Huesman, Ronald L. Jr.; Kellogg, John P.. (2007). Modeling the Incidence and Timing of Student Attrition: A Survival Analysis Approach to Retention Analysis. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159767
Priced Out? Does Financial Aid Affect Student Success?
No full textPresented at the 2009 National Symposium on Student Retention. The Symposium was sponsored by the Consortium for Student Data Exchange (CSRDE), Buffalo, NY, October 1-2, 2009.Jones-White, Daniel R.; Radcliffe, Peter M.; Lorenz, Linda. (2009). Priced Out? Does Financial Aid Affect Student Success?. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159748
Priced Out? Does Financial Aid Affect Student Success?
No full textPresented at the 2010 annual Association of Institutional Research (AIR) forum, Chicago, IL, May 30-June 2, 2010.Jones-White, Daniel R.; Radcliffe, Peter M.; Lorenz, Linda. (2010). Priced Out? Does Financial Aid Affect Student Success?. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159744
Modeling the Incidence and Timing of Student Attrition: A Survival Analysis Approach to Retention Analysis
No full textPresented at the Association for Institutional Research Upper Midwest (AIRUM) annual meeting, Bloomington, MN, November 2-3, 2006.Radcliffe, Peter M.; Huesman, Ronald L. Jr.; Kellogg, John P.. (2006). Modeling the Incidence and Timing of Student Attrition: A Survival Analysis Approach to Retention Analysis. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159768
Identifying Students at Risk: Utilizing Survival Analysis to Study Student Athlete Attrition
No full textPaper presented at the National Symposium on Student Retention, Bloomington, MN, October 9-11, 2006. The Symposium was sponsored by the Consortium for Student Data Exchange (CSRDE).Radcliffe, Peter M.; Huesman, Ronald L. Jr.; Kellogg, John P.. (2006). Identifying Students at Risk: Utilizing Survival Analysis to Study Student Athlete Attrition. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159769
Redefining Student Success: Assessing Different Multinomial Regression Techniques for the Study of Student Retention and Graduation Across Institutions of Higher Education
No full textPresented at the Association of Institutional Research (AIR) annual forum, Seattle, WA, May 24-28, 2008.Jones-White, Daniel R.; Radcliffe, Peter M.; Huesman, Ronald L. Jr.; Kellogg, John P.. (2008). Redefining Student Success: Assessing Different Multinomial Regression Techniques for the Study of Student Retention and Graduation Across Institutions of Higher Education. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159760
Apples to Apples: Using AAUDE Faculty-by-CIP Data to Account for Discipline Differences in Faculty Salaries
No full textPresented at the Association of Institutional Research (AIR) annual forum, Toronto, Canada, May 25, 2011.Popular methods that attempt to account for discipline in salary studies such as subdividing the population by discipline or market proxies that estimate supply and demand of new Ph.D.s fall short of their intended explanatory power or lead to inappropriate conclusions due to misunderstandings of the nature of academic faculty markets. This study demonstrates how the single variable: average peer institution faculty salary by CIP within rank – obtained from the American Association of Universities Data Exchange (AAUDE) – dramatically improves the predictive power of a salary model, accounting for more than 80% of the variance for assistant professor salaries alone.Goldfine, Leonard S.; Radcliffe, Peter M.. (2011). Apples to Apples: Using AAUDE Faculty-by-CIP Data to Account for Discipline Differences in Faculty Salaries. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159727
Identifying Factors Related to Student Success: Utilizing Multinomial Logit Regression to Study Graduation in Higher Education
No full textPresented at the Association for Institutional Research Upper Midwest (AIRUM) annual meeting, Bloomington, MN, October 25-26, 2007.Huesman, Ronald L. Jr.; Radcliffe, Peter M.; Jones-White, Daniel R.; Kellogg, John P.; Lee, Giljae. (2007). Identifying Factors Related to Student Success: Utilizing Multinomial Logit Regression to Study Graduation in Higher Education. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159764
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
- …
