Paul von Hippel’s research interests include educational inequality and the relationship between schooling, health, and obesity. He is currently working on a WT Grant-funded study on the growth of achievement gaps, as well as a study, funded by the Stanford Center on Poverty and Inequality, on financial inequality between families and between school districts. He was a co-investigator on a state-funded project that evaluated the teacher preparation programs in Texas, and he now serves as a research advisor to a multisite randomized study evaluating the impact of summer learning programs. He is a three-time winner of best article awards from the education and methodology sections of the American Sociological Association.
Von Hippel is an expert on research design and on statistical methods for missing data. Before his academic career, he was a data scientist who developed fraud-detection scores for banks including JP Morgan Chase and the Bank of America.
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Ph.D. in Sociology, Ohio State University; M.A.S. in Statistics, Ohio State University; Ph.D. in Computer-Based Music Research, Stanford University; B.A. in Music, Yale University
Assistant Professor of Public Affairs, The LBJ School of Public Affairs
Research Statistician, Department of Sociology and Initiative in Population Research, Ohio State University (2002-2005); Senior Fraud and Risk Analyst, CheckFree Services Corporation and J.P. Morgan Chase (2006-2010)
Google Scholar Citations Page
- von Hippel, P. T. & Bradbury, K. (2015). “The effects of school physical education grants on obesity, fitness, and achievement.” Preventive Medicine 78: 45-51.
- von Hippel, P.T., Scarpino, S.V., & Holas, I. (2016). “Robust estimation of inequality from binned incomes.” Sociological Methodology, accepted. Also available as arXiv e-print 1402-4061.
- von Hippel, P. T., The heterogeneity statistic I2 can be biased in small meta-analyses, BMC Medical Research Methodology, April 2015, 15:35.
- von Hippel, P. T., Nahhas, R. W. and Czerwinski, S. A. (2015), How much do children's body mass indices change over intervals of 6–12 months? Statistics from before and during the obesity epidemic. Pediatric Obesity. doi: 10.1111/ijpo.12008
- von Hippel, P. T. and Rebecca Benson. "Obesity and the Natural Environment Across US Counties," American Journal of Public Health: July 2014, Vol. 104, No. 7, pp. 1287-1293.
- von Hippel, P. T. and Osborne, Cynthia and Arnold Lincove, Jane and Bellows, Laura and Mills, Nicholas, "The Challenges of Seeking Exceptional Teacher Preparation Programs Among Many Noisy Estimates" (October 7, 2014).
- von Hippel, P. T., and Lynch, J.L. (2014) "Efficiency Gains from Using Auxiliary Variables in Imputation" arXiv:1311.5249 [stat.ME].
- von Hippel, P. T., and Lynch, J.L. (2014) “Why are educated adults slim—causation or selection?” Social Science and Medicine, accepted.
- von Hippel, P.T. (2015). “New confidence intervals and bias calculation show that maximum likelihood can beat multiple imputation in small samples.” Structural Equation Modeling, accepted. Also available as arXiv e-print 1307-5835.
- von Hippel, P.T. (2013). "Extending the history of child obesity in the United States: The Fels longitudinal study, birth years 1930 to 1993." Obesity.
- von Hippel, P.T. (2012). “A simpler standard error formula for multiple imputation based on a maximum likelihood estimate.” arXiv:1210.0870 [stat.ME].
- von Hippel, P.T., Holas, I.. & Scarpino, S.V. (2012). “Estimation with binned data.” arXiv:1210.0200 [stat.ME].
- von Hippel, P.T. (2012) “The bias and efficiency of incomplete-data estimators in small univariate normal samples.” arXiv:1204.3132 [math.ST].
- von Hippel, P. T., and Lynch, J. L. (2012) “A simplified equation for adult BMI growth, and its use to adjust BMI for age.” International Journal of Epidemiology, forthcoming.
- von Hippel, Paul T. 2013. “Should a Normal Imputation Model Be Modified to Impute Skewed Variables?” Sociological Methods and Research, February 2013 vol. 42 no. 1 105-138.
- von Hippel, P.T. (2010). "Skewness." In Lovric, M., Ed., International Encyclopedia of Statistical Science. New York: Springer.
- von Hippel, P.T. (2009). "How To Impute Squares, Interactions, and Other Transformed Variables." Sociological Methodology 39.
- von Hippel, P.T. (2009). "Achievement, Learning, and Seasonal Impact as Measures of School Effectiveness: It's Better To Be Valid Than Reliable." School Effectiveness and School Improvement 20(2), 187-213.
- Downey, D.B., von Hippel, P.T., & Hughes, M.M. (2008). "Are 'Failing' Schools Really Failing? Removing the Influence of Non-School Factors from Measures of School Quality." Sociology of Education 81(3), 242-270.
*James Coleman Award, Education Section, American Sociological Association, 2009.
- von Hippel, P.T. (2007). “ Regression with Missing Ys: An Improved Strategy for Analyzing Multiply-Imputed Data.” Sociological Methodology, 37(1).*
*Clifford Clogg Award, Methodology Section, American Sociological Association, 2007.
- von Hippel, P.T., Powell, B., Downey, D.B., & Rowland, N. (2007). “The Effect of School on Overweight in Childhood: Gains in children’s body mass index during the school year and during summer vacation.” American Journal of Public Health 97(4), 796-802.
- von Hippel, P.T. (2005). " Mean, Median, and Skew: Correcting a Textbook Rule." Journal of Statistics Education, 13(2).
- von Hippel, P.T. (2005). "How Many Imputations Are Needed? A Comment on Hershberger and Fisher (2003)." Structural Equation Modeling, 12(2), 334-335.
- Downey, D.B., von Hippel, P.T., and Broh, B. (2004). "Are Schools the Great Equalizer? School and Non-School Sources of Inequality in Cognitive Skills." American Sociological Review, 69(5), 613-635.*
*William Waller Award, Sociology of Education section, American Sociological Association, 2005.
- von Hippel, P.T. (2004). " Biases in SPSS 12.0 Missing Value Analysis." The American Statistician 58(2), 160-164.
- von Hippel, P.T. (2004). "School Accountability [a comment on Kane and Staiger (2002)]." Journal of Economic Perspectives, 18(2), 275-276.
- von Hippel, P.T. (2003). Four articles in Encyclopedia of Social Science Research Methods (Lewis-Beck, Bryman, and Liao, eds.). Thousand Oaks, CA: Sage.
- von Hippel, P.T. (2000). "Redefining Pitch Proximity: Tessitura and Mobility as Constraints on Melodic Intervals." Music Perception, Vol. 17, No. 3, 315-327.
- von Hippel, P.T. (2000). "Why Do Skips Precede Reversals? The Effect of Tessitura on Melodic Structure." Music Perception, Vol. 18, No. 1, 59-85.
- von Hippel, P.T. (2000). "Questioning a Melodic Archetype: Do Listeners Use Gap-Fill to Classify Melodies?" Music Perception, Vol. 18, No. 2, 139-153.
- von Hippel, P.T. (2002). "Melodic-Expectations Rules as Learned Heuristics." Proceedings of the 7th International Conference on Music Perception and Cognition, Sydney 2002.
- von Hippel, P.T. (2002). "How Rare is Symmetry in Musical 12-Tone Rows?" The American Mathematical Monthly, Vol. 110, No. 2, 124-132.
- Aarden, B. and von Hippel, P.T. (2004). "Rules for Chord Doubling (and Spacing): Which Ones Do We Need?" Music Theory Online, Vol. 10, No. 2.
- Aarden, B. and von Hippel, P.T. (2004). "Rules for Chord Doubling (and Spacing): A Reply To Wibberley." Music Theory Online, Vol. 10, No. 3.