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Paul von Hippel

Paul  von Hippel

Assistant Professor of Public Affairs

Contact Info

(512) 232-3650
SRH 3.251

Paul von Hippel studies educational inequality and the relationship between schooling, health, and obesity. He is an expert on research design and missing data, and a three-time winner of best article awards from the education and methodology sections of the American Sociological Association. 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.

Download a PDF of Paul von Hippel's CV


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

Current Positions

Associate Professor of Public Affairs, The LBJ School of Public Affairs

Previous Positions

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)


Invited book chapter

  1. von Hippel, P.T. (2016). “Year-round school calendars: Effects on summer learning, achievement, families, and teachers.” Chapter 13 in Alexander, K., Pitcock, S. & Boulay, M. (eds.). Summer Learning and Summer Learning Loss: Theory, Research, and Practice. New York: Teachers College Press. Also available as SSRN working paper 2766106.

Peer-reviewed journal articles (†graduate student coauthor)

  1. Lynch, J.L. & von Hippel, P.T. (2016) “An education gradient in health, a health gradient in education, or a confounded gradient in both?” Social Science and Medicine, accepted. Also available as SSRN working paper 2583971.

  2. von Hippel, P.T., †Scarpino, S.V., & †Holas, I. (2016). “Robust estimation of inequality from binned incomes.” Sociological Methodology, accepted and published online ahead of print. Also available as arXiv e-print 1402.4061.

  3. von Hippel, P. T. & †Bradbury, K. (2015). “The effects of school physical education grants on obesity, fitness, and achievement.” Preventive Medicine 78: 45-51.

  4. von Hippel, P.T. (2015). “New confidence intervals and bias calculations show that maximum likelihood can beat multiple imputation in small samples.” Structural Equation Modeling, accepted and published online ahead of print. Also available as arXiv e-print 1307.5835.

  5. von Hippel, P.T. (2015). “The heterogeneity statistic I2 can be biased in small meta-analyses.” BMC Medical Research Methodology 15:35.

  6. von Hippel, P. T., Nahhas, R., & Czerwinski, S. (2015). “How much do children’s body mass indices change over periods of 6-12 months? Statistics from before and during the obesity epidemic.” Pediatric Obesity.

  7. von Hippel, P. T. & †Benson, R. (2014). “Obesity and the natural environment across US counties.” American Journal of Public Health, 104(7):1287-1293. PubMed 24832148.

    a.     Comment by Adam Drewnowski: “Sunscreen or Gore-Tex?” American Journal of Public Health, September 2014.
    b.     Our reply to Drewnowski: “Hot properties, cold properties,” American Journal of Public Health, September 2014.

  8. von Hippel, P. T., & Lynch, J.L. (2014). “Why are educated adults slim—causation or selection?” Social Science and Medicine, 105: 131-139. PubMed 24524908. Also available as SSRN working paper 2054843.

  9. von Hippel, P. T., & Nahhas, R. (2013). “Extending the history of child obesity in the United States: The Fels Longitudinal Study, birth years 1930-1993.” Obesity 21(1): 2153-2156. PubMed 23512972.

  10. von Hippel, P.T. (2013). “The bias and efficiency of incomplete-data estimators in small univariate normal samples.” Sociological Methods and Research, 42(4): 531-558. Also available as arXiv e-print 1204.3132.

  11. von Hippel, P. T. (2013). “Should a normal imputation model be modified to impute skewed variables?Sociological Methods and Research, 42(1), 105-138.

  12. von Hippel, P. T., & Lynch, J. L. (2012). “A simplified equation for adult BMI growth, and its use to adjust BMI for age.” International Journal of Epidemiology 41(3): 888-890.

  13. von Hippel, P. T. (2009). “How to impute interactions, squares, and other transformed variables.Sociological Methodology 39, 265-291.

  14. 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.

  15. Downey, D.B., von Hippel, P.T. (equal contributors) & †Hughes, M. (2008). “Are ‘failing’ schools really failing?Sociology of Education 81(3), 242-270.

  16. von Hippel, P.T. (2007). “Regression with missing Ys: An improved strategy for analyzing multiply-imputed data” Sociological Methodology 37, 83-117.

  17. 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.

  18. von Hippel, P.T. (2005). “Mean, median, and skew: Correcting a textbook rule.” Journal of Statistics Education 13(2).

    1. With comment by Lawrence Lesser, Journal of Statistics Education 13(3).

  19. 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.
  20. von Hippel, P.T. (2004). “Biases in SPSS 12.0 Missing Values Analysis.” The American Statistician 58(2), 160-164.
  21. †Aarden, B., & von Hippel, P.T. (2004). “Rules for chord-tone doubling (and spacing): Which ones do we need?Music Theory Online 10.2.

    a.     Comment by Roger Wibberley, Music Theory Online 10.3.

    b.     Reply by von Hippel & Aarden, Music Theory Online 10.4.
  22. Hunter, D.J., & von Hippel, P.T. (2003). “How rare is symmetry in musical 12-tone rows?American Mathematical Monthly 110(2), 124-132.

  23. von Hippel, P.T. (2000). “Questioning a melodic archetype: Do listeners use gap-fill to classify melodies?Music Perception 18(2), 139-153.

  24. von Hippel, P.T., & Huron, D. (2000). “Why do skips precede reversals? The effect of tessitura constraints on melodic structure.” Music Perception 18(1), 59-85.

  25. von Hippel, P.T. (2000). “Redefining pitch proximity: Tessitura and mobility as constraints on melodic intervals.” Music Perception 17(3), 315-327.

Articles under review

  1. von Hippel, P. T. & Workman, J. “Children’s obesity prevalence grows during summer vacations, but not during school years, from kindergarten through second grade. ” Submitted to JAMA Pediatrics January 26, 2016.
  2. von Hippel, P. T., †Bellows. L., Osborne, C., Lincove, J., & Mills, N. “Teacher quality differences between teacher preparation programs: How big? How reliable? Which programs are different?” Submitted March 2015 to Economics of Education Review. Revision requested May 2015; resubmitted October 2015. Second revision requested December 15, 2015. Also available as SSRN working paper 2506935.

Articles in preparation

  1. von Hippel, P. T., Hamrock, C., & Kumar, M. “Do test score gaps grow before, during, or between the school years?” Planned submission to American Journal of Sociology.

  2. von Hippel, P.T., Holas, I., & Scarpino, S. V. “Secession of the successful or millionaires next door? Family income inequality within and between US school districts, 1970- 2009.” Planned submission to Sociological Science.

  3. von Hippel, P. T. & Quezada-Hofflinger, A. “US school district revenues, 1970-2009: Progressive equalization or persistent inequality?” Planned submission to American Sociological Review.

  4. von Hippel, P. T. & Wagner, C. “After Project STAR, Tennessee reduced class sizes and raised children’s test scores.” Planned submission to Journal of Policy Analysis and Management.

  5. Quezada-Hofflinger, A. & von Hippel, P.T. “The effects of expanding school choice on achievement, segregation, and inequality: Chile from 1999 to 2013.” Planned submission to Journal of Policy Analysis and Management.

Statistical methods
  1. von Hippel, P. T. “Maximum likelihood multiple imputation.” Planned submission to Annals of Statistics.
  1. von Hippel, P. T., Sparks, C., & †Pattison, E. “Why are some US counties more obese than others—environment or demographics?” Planned submission to Social Science and Medicine.

Letters and comments

  1. von Hippel, P. T. (2013). “Statin therapy for hyperlipidemia.” Letter to Journal of the American Medical Association 310(11): 1185.

  2. von Hippel, P.T. (2005). “How many imputations are needed? A comment on Hershberger and Fisher.” Structural Equation Modeling, 12(2), 334-335.

  3. von Hippel, P.T. (2004). “School Accountability [a comment on Kane and Staiger].” Journal of Economic Perspectives 18(2), 275-276.

Encyclopedia articles

  1. von Hippel, P. T. (2014). “Mean Log Deviation.”

  2. von Hippel, P. T. (2010). “Skewness.” International Encyclopedia of Statistical Science (M. Lovric, Ed.). New York: Springer.

  3. von Hippel, P.T. (2002) Four entries in the Encyclopedia of Social Science Research Methods (M. Lewis-Beck, A. Bryman, T.F. Liao, eds.). Thousand Oaks, CA: Sage.

  • “Critical value."

  • “Difference of proportions.”

  • “Expected value.”

  • “Normalization.”


  1. Evidence-Based Policy: Texas Lags But Should Lead” Aug. 2015
  • Dallas Morning News August
  • Forth Worth Star-Telegram
  • Austin American-Statesman

Data journalism

  1. What would be fair odds on American Pharoah?Thoroughbred Racing Commentary. 2015
  2. Should we all take a bit of lithium?!” (with Sheila Olmstead). Resources for the Future.
  3. Tweedledum vs. Tweedledee? Ralph Nader’s own data show he’s wrong about the major parties.” 2004
  4. What are doctors really paying for malpractice insurance?” 2004

Conference Proceedings

  1. von Hippel, P.T. (2002). “Melodic Expectation Rules as Learned Heuristics.” Proceedings of the 7th International Conference on Music Perception and Cognition. Adelaide: Causal Productions.

Book reviews

  1. von Hippel, P.T. (2006). “Jan Beran, Statistics in Musicology.” Empirical Musicology Review 1(1).

  2. von Hippel, P.T. (2003). “Chava Frankfort-Nachmias and Anna Leon-Guerrero: Statistics for a Diverse Society.” Teaching Sociology, 31(1), 128-129.

  3. von Hippel, P.T. (2000). “Jerrold Levinson: Music in the Moment.” Music Analysis, 19(1): 137-143.

Working papers (excluding those that have also been published as journal articles)

  1. von Hippel, P.T., & Lynch, J.L. (2013). “Efficiency gains from using auxiliary variables in imputation.” arXiv e-print 1311.5249.

  2. von Hippel, P.T., Holas, I.. & Scarpino, S.V. (2012). “SAS macros for estimation with binned data.” arXiv e-print 1210.0200.

Government reports

  1. Osborne, C., Lincove, J. von Hippel, P.T., Mills, N., Dillon, A., Bellows, L. (2012). Educator Preparation Programs’ Influence on Student Achievement. Report to the Texas Education Agency. Austin, TX: Project on Educator Effectiveness and Quality (PEEQ).

Research Briefs

  1. “Summertime and weight gain.” (2007). Center for Summer Learning, Baltimore, MD.

Published software

  1. von Hippel, P.T. & Powers, D.E. (2015). “The rpme command for Stata.” This implements the robust Pareto midpoint estimator developed by von Hippel, Scarpino, and Holas (2015).

  2. Scarpino, S., von Hippel, P.T., & Holas, I. (2014). “The binequality package for R.” This implements the multimodel GB estimator developed by von Hippel, Scarpino, and Holas (2014).

  3. von Hippel, P.T. (2007). “The %mid macro for SAS.” This implements the multiple imputation with deletion (MID) method developed by von Hippel (2007). The macro is in that article’s Appendix.

Published data

  1. London, J., von Hippel, P.T., Huron, D., Cartano, J., Kingery, K., Olsen, B., & Santelli, T. (2001). “Row forms in the serial works of Schoenberg, Berg, and Webern.” Stanford, CA: Center for Computer Assisted Research in the Humanities (

  2. von Hippel, P.T. (1998). “42 Ojibway songs in the Humdrum **kern representation: Electronic transcriptions from the Densmore collections.” Stanford, CA: Center for Computer Assisted Research in the Humanities (