Thank you for visiting my page. I am an Associate Professor in the Department of Statistics at the University of Virginia.
My research aims to understand issues around the coordinated analysis of data in a wide variety of forms, and to develop conceptions of statistical knowledge and accompanying statistical practices that are amenable to integration with knowledge and practices from alternative traditions of inquiry. Such traditions include statistics for marginalized groups, various forms of qualitative inquiry, mixed methods research, and diffractive analysis. In all cases the social context of inquiry is a crucial concern. This work overlaps to some extent with my additional interests in Bayesian model choice and applications in forensic science. Some of my older work examines issues in functional data analysis and classical shrinkage estimation.
Recent papers, preprints, and presentations, most of which are accessible through the links appearing at the bottom of this page, are as follows:
Note: The first two presentations listed below describe pieces of an idea in development, which I call Statistics Under a Qualitative Mental Model. The two presentations substantially overlap; distinctions are that the 2023 presentation covers background material and motivation in greater detail, while the 2024 presentation brings in core ideas. Development of the idea is near to completion and soon to be described in a full manuscript.
Spitzner, D. J. (March 1, 2024). Statistical practice under a qualitative mental model [Presentation]. Presentation to the Qualitative Report 15th Annual Conference in Fort Lauderdale, Florida, USA
Spitzner, D. J. (April 6, 2023). Statistical practice under a qualitative mental model [Presentation]. Presentation to the 7th International Qualitative Research in Management and Organization Conference in Albuquerque, New Mexico, USA
Spitzner, D. J. (June 14, 2023). Recent methodological advances in Bayes factors for use in forensic analysis and reporting [Presentation]. Presentation to the 11th International Conference on Forensic Inference and Statistics in Lund, Skåne County, Sweden
Spitzner, D. J. (February 18, 2021). Decolonizing statistical analysis [Presentation]. Presentation to the 11th Annual African, African American & Diaspora Studies Interdisciplinary Conference
Spitzner, D. J. (September 9, 2020). Socially-inclusive foundations of statistics [Presentation]. Presentation to the Humanities Informatics Lab Final Showcase: Human & Machine Intelligence
A selection of my other favorite published papers are as follows:
Spitzner, D. J., and Meixner, C. (2023). Mixed methods research in global public health. In P. Liamputtong (Ed.), Handbook of Social Sciences and Global Public Health. Cham: Springer. DOI: 10.1007/978-3-030-96778-9_52-1.
Spitzner, D. J. (2023b). Upending quantitative methodology for use in global public health. In P. Liamputtong (Ed.), Handbook of Social Sciences and Global Public Health. Cham: Springer. DOI: 10.1007/978-3-030-96778-9_51-1.
Spitzner, D. J. (2023c). Calibrated Bayes factors under flexible priors. Statistical Methods & Applications. DOI: 10.1007/s10260-023-00683-4. (link)
Meixner, C., and Spitzner, D. J. (2022). Leveraging the power of online qualitative inquiry in mixed methods research: Novel prospects and challenges amidst COVID-19. Journal of Mixed Methods Research. DOI: 10.1177/15586898221084504
Spitzner, D. J. (2023a). A statistical basis for reporting strength of evidence as pool reduction. The American Statistician, 77:1, 62-71. DOI: 10.1080/00031305.2022.2026478
Meixner, C., & Spitzner, D. J. (2021). Mixed methods research and social inclusion. In P. Liamputtong (Ed.), Handbook of social inclusion: research and practices in health and social sciences. Cham: Springer. DOI: 10.1007/978-3-030-48277-0_19-1
Spitzner, D. J. (2021). Socially-inclusive foundations of statistics: an autoethnography. In P. Liamputtong (Ed.), Handbook of social inclusion: research and practices in health and social sciences. Cham: Springer. DOI: 10.1007/978-3-030-48277-0_17-1 (Preprint available below)
Spitzner, D. J. & Meixner, C. (2021). Significant conversations, significant others: Intimate dialogues about teaching statistics. International Journal for Academic Development. DOI: 10.1080/1360144X.2021.1954931
Spitzner, D. J. (2019). “Subjective Bayesian testing using calibrated prior probabilities.” Brazilian Journal of Probability and Statistics. 33(4), 861-893. DOI: 10.1214/18-BJPS424
Spitzner, D. J. (2011). Neutral-data comparisons for Bayesian testing. Bayesian Analysis, 6:603-638. DOI: 10.1214/11-BA623
Spitzner, D. J. (2008). “A powerful test based on tapering for use in functional data analysis.” Electronic Journal of Statistics. 2:939-962.
Spitzner, D. J. (2005). “Risk-reducing hierarchical shrinkage for generalized linear models.” Journal of the Royal Statistics Society Series B, 67:1-14.
Spitzner, D. J., Marron, J. S., and Essick, G. K. (2003). “Mixed-model functional ANOVA for studying human tactile perception.” Journal of the American Statistical Association, 98:263-272.
Selected technical reports, also accessible through the links below, are as follows:
Spitzner, D. J. (2014a). Adjusting for multiplicities in variable selection using neutral-data comparisons. University of Virginia Department of Statistics, Technical Report Series, 14-02. Some of this paper's ideas are developed in Spitzner (2019).
Spitzner, D. J. (2014b). Neutral-data comparisons defining a spectrum between Bayes factors and the Schwarz criterion. University of Virginia Department of Statistics, Technical Report Series, 14-01. Some of this paper's ideas are developed in Spitzner (2019).