KU Edwards Campus A-Z
  1. A
  2. B
  3. C
  4. D
  5. E
  6. F
  7. G
  8. H
  9. I
  10. J
  11. K
  12. L
  13. M
  14. N
  15. O
  16. P
  17. Q
  18. R
  19. S
  20. T
  21. U
  22. V
  23. W
  24. X
  25. Y
  26. Z

Joshua Habiger, PhD

Associate Professor, Department of Biostatistics
Primary office:
913-588-4703


Personal Mission Statement

High throughput technology, such as imaging, sequencing and data mining technology, is used to generate high dimensional (HD) data sets that are rich in information.  However, this information is often difficult to extract due to the size and messy nature of the data.  For example, measurements on thousands or even millions of attributes are often taken on a handful of subjects across multiple treatment groups, and data may be missing, categorical, correlated, and/or heterogeneous.  My personal mission is to develop and apply practical methods that efficiently and soundly extract information from HD data, and to inspire and train the next generation of statisticians who will be responsible for analyzing larger, more complex and even more exciting data.

Research

Research Focus

High Dimensional Data, Multiple Testing, Categorical Data, Multivariate Methods, Nonparametric Methods, Empirical Bayes Methods, Imputation

Selected Publications

Top 13 publications

Lauter, N., Mosco, M., Habiger, J., and Moose, S. (2008). Quantitative genetic dissection of shoot architecture in maize: Towards a functional genomics approach. The Plant Genome, 1(2), 99-110. https://dl.sciencesocieties.org/publications/tpg/articles/1/2/99

Cui, X., Jin, Y., Hofseth, A., Pe~na, E., Habiger, J., Chumanevich, A., Nagarakatti, M., Nagarakatti, P., Singh, U., and Hofseth, H. (2010). Resveratrol suppresses colitis and colon cancer associated with colitis. Cancer Prevention Research, 3(1), 549-559. http://cancerpreventionresearch.aacrjournals.org/content/early/2010/03/20/1940-6207.CAPR-09-0117

Cui, X., Jin, Y., Hofseth, A., Pe~na, E., Habiger, J., Chumanevich, A., Nagarakatti, M., Nagarakatti, P., Singh, U. and Hofseth, H. (2010). Mechanistic insight into the ability of American ginseng to suppress colon cancer associated with colitis. Carcinogenesis, 31(10), 1734-1741. http://carcin.oxfordjournals.org/content/31/10/1734

Peña, E., Habiger, J. and Wu, W. (2011). Power-enhanced multiple decision functions controlling family-wise error and false discovery rates. Annals of Statistics, 39(1), 556-583. http://projecteuclid.org/DPubS?service=UI&version=1.0&verb=Display&handle=euclid.aos/1297779856

Habiger, J. and Peña, E. (2011). Randomised p-values and nonparametric procedures in multiple testing. Journal of Nonparametric Statistics, 23(3), 583-604. http://www.tandfonline.com/doi/abs/10.1080/10485252.2010.482154#.V4QaLUYrJaQ

Habiger, J. (2012). A method for modifying multiple testing procedures. Journal of Statistical Planning and Inference, 142(7), 2227-2231. http://www.sciencedirect.com/science/article/pii/S0378375812000572

Anderson M. and Habiger J. (2012). Characterization and identi_cation of productivity associated rhizobacteria in wheat. Applied and Environmental Microbiology, 78(12), 4434-4446. http://aem.asm.org/content/78/12/4434.short

Habiger, J., McCann, M. and Tebbs, J. (2013). On optimal confidence sets for parameters in discrete distributions. Statistics and Probability Letters, 83(1), 297-303. http://www.sciencedirect.com/science/article/pii/S0167715212003641

Robbins, M., Ghosh, S. and Habiger, J. (2013). Imputation in high dimensional economic data: An introduction and comparison of methods as applied to the Agricultural Resource Management Survey. Journal of the American Statistical Association, 108(501), 81-95. http://www.tandfonline.com/doi/abs/10.1080/01621459.2012.734158

Habiger, J. and Peña, E. (2014). Compound p-values for multiple testing procedures. Journal of Multivariate Analysis, 126, 153-166. http://www.sciencedirect.com/science/article/pii/S0047259X14000153

Habiger, J. and Adekepdjou, A. (2014). Optimal rejection curves for _nite false discovery rate control. Statistics and Probability Letters, 94, 21-28. http://www.sciencedirect.com/science/article/pii/S016771521400248X

Peña, E., Habiger, J. and Wu, W. (2015). Classes of multiple decision functions strongly controlling FWER and FDR. Metrika, 78(5), 563-595. http://link.springer.com/article/10.1007%2Fs00184-014-0516-6

Habiger, J. (2015). Multiple test functions and adjusted p-values for test statistics with discrete distributions. Journal of Statistical Planning and Inference, 167, 1-13. http://www.sciencedirect.com/science/article/pii/S0378375815001172