Hisashi NOMA, MPH, PhD



  1. Noma, H., Matsui, S., Omori, T. and Sato, T. (2010). Bayesian ranking and selection methods using hierarchical mixture models in microarray studies. Biostatistics 11: 281-289. DOI: 10.1093/biostatistics/kxp047
  2. Matsui, S. and Noma, H. (2011). Estimation and selection in high-dimensional genomic studies for developing molecular diagnostics. Biostatistics 12: 223-233. DOI: 10.1093/biostatistics/kxq057
  3. Matsui, S. and Noma, H. (2011). Estimating effect sizes of differentially expressed genes for power and sample size assessments in microarray experiments. Biometrics 67: 1225-1235. DOI: 10.1111/j.1541-0420.2011.01618.x
  4. Noma, H. (2011). Confidence intervals for a random-effects meta-analysis based on Bartlett-type corrections. Statistics in Medicine 30: 3304-3312. DOI: 10.1002/sim.4350
  5. Noma, H. and Matsui, S. (2012). The optimal discovery procedure in multiple significance testing: an empirical Bayes approach. Statistics in Medicine 31: 165-176. DOI: 10.1002/sim.4375
  6. Noma, H. and Matsui, S. (2013). Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies. Statistics in Medicine 32: 1904-1916. DOI: 10.1002/sim.5718
  7. Miura, T., Noma, H., Furukawa, T. A., Mitsuyasu, H., Tanaka, S., Stockton, S., Salanti, G., Motomura, K., Shimano-Katsuki, S., Leucht, S., Cipriani, A., Geddes, J. R. and Kanba, S. (2014). Comparative efficacy and tolerability of pharmacological treatments in the maintenance treatment of bipolar disorder: a network meta-analysis. Lancet Psychiatry 1: 351-359. DOI: 10.1016/S2215-0366(14)70314-1.
  8. Noma, H. and Tanaka, S. (2014). Analysis of case-cohort designs with binary outcomes: Improving efficiency using whole-cohort auxiliary information. Statistical Methods in Medical Research, DOI: 10.1177/0962280214556175.
  9. Noma, H., Tanaka, S., Matsui, S., Cipriani, A. and Furukawa, T. A. (2017). Quantifying indirect evidence in network meta-analysis. Statistics in Medicine 36: 917-927. DOI: 10.1002/sim.7187.
  10. Matsui, S., Noma, H., Qu, P., Sakai, Y., Matsui, K., Heuck, C. and Crowley, J. (2017). Multi-subgroup gene screening using semi-parametric hierarchical mixture models and the optimal discovery procedure: application to a randomized clinical trial in multiple myeloma. Biometrics, DOI: 10.1111/biom.12716.