The Institute of Statistical Mathematics, Tokyo, Japan

Hisashi Noma's Homepage



     Frontiers of Biostatistical Methods and Applications in Clinical Oncology
      Edited by Matsui, S. and Crowley, J.

      1st Edition, September 2017

      489 PagesHardcover
      ISBN 978-9811001246 Springer, New York



      ISBN 978-4000298476 岩波書店,東京

     Design and Analysis of Clinical Trials for Predictive Medicine
      Edited by Matsui, S., Buyse, M. and Simon, R.

      1st Edition, April 2015

      400 Pages, Hardcover
      ISBN 978-1466558151 Chapman and Hall/CRC, Boca Raton

     Statistical Diagnostics for Cancer
      Edited by Emmert-Streib, F. and Dehmer, M.

      1st Edition, January 2013

      312 Pages, Hardcover
      ISBN 978-3527332625 Wiley-VCH, Weinheim

     Handbook of Statistics in Clinical Oncology
      Edited by Crowley, J. and Hoering, A.
      3rd Edition, April 2012

      657 Pages, Hardcover
      ISBN 978-1439862001 Chapman & Hall/CRC, Boca Raton

Selected Papers

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. Furukawa, T. A., Noma, H., Caldwell, D., Honyashiki, M., Shinohara, K., Imai, H., Hunot, V. and Churchill, R. (2014). Is a waiting list control a nocebo condition in psychotherapy trials? A contribution from network meta-analysis. Acta Psychiatrica Scandinavica 130: 181-192. DOI: 10.1111/acps.12275. [Featured as "Article of the Month" of Acta Psychiatrica Scandinavica]
8. 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. [Press Release; Kyushu University, 2014/09/19]
9. 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.
10. 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.
11. 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.

Google Scholar Citation: Hisashi Noma@The Institute of Statistical Mathematics

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