Abstract
Computational statistics, supported by computing power and availability of efficient methodology, techniques and algorithms on the statistical side and by the perception on the need of valid data analysis and data interpretation on the biomedical side, has invaded in a very short time many cutting edge research areas of molecular biomedicine. Two salient cutting edge biomedical research questions demonstrate the increasing role and decisive impact of computational statistics. The role of well designed and well communicated simulation studies is emphasized and computational statistics is put into the framework of the International Association of Statistical Computing (IASC) and special issues on Computational Statistics within Clinical Research launched by the journal Computational Statistics and Data Analysis (CSDA).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
BENJAMINI, Y. and HOCHBERG, Y. (1995): Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B 57, 289-300.
BENNER, A., ZUCKNICK, M., HIELSCHER, T., ITTRICH, C. and MANSMANN, U.(2010): High-dimensional Cox models: the choice of penalty as part of the model building process. Biometrical Journal 52, 50-69.
BINDER, H. and SCHUMACHER, M. (2008): Adapting Prediction Error Estimates for Biased Complexity Selection in High-Dimensional Bootstrap Samples. Statistical Applications in Genetics and Molecular Biology 7 (1) Article 12. DOI: 10.2202/1544-6115.1346
BOULESTEIX, A.L., STROBL, C., AUGUSTIN, T., DAUMER, M. (2008): Evaluating microarray-based classifiers: An overview. Cancer Informatics 6, 77-97.
BOVEHSAD, H.M., NYGARD, M., STORVOLD, S., ALDRIN, H.L.L., BORGAN, O., FRIGESSI, A. and LINGGIAERDE, O.C.C. (2007): Predicting survival from microarray data - a comparative study. Bioinformatics, 23(16), 2080-2087
BRETZ, F., KOENIG, F., BRANNATH, W, GLIMM,E. and POSCH, M. (2009: Tutorial in biostatistics: Adaptive designs for confirmatory clinical trials, Statistics in Medicine 28, 1181-1217.
CHAMBERS, J. (1999): Computing with data: concepts and challenges. The American Statistician 53, 73-84.
DICKHAUS, T., BLANCHARD, G., HACK, N., KONIETSCHKE, F., ROHMEYER, K., ROSENBLATT, J., SCHEER, M. and WERFT, W. (2010): μTOSS - Multiple hypotheses testing in an open software system. 2nd Joint Statistical Meeting DAGSTAT Statistics under one Umbrella March 23-26, 2010, Technical University, Dortmund, p 77 (abstract).
DUDOIT, S, and Van DER LAAN, M. (2007) Multiple Testing Procedures with Applications to Genomic. Springer, New York
EDLER, L. (2005): Computational Statistics und Biometrie. Wer treibt wen? GMDS Medizinische Informatik, Biometrie und Epidemiologie 1 (2) doi10 -(20050620), 2005.
EDLER, L, WAHRENDORF, J. and BERGER, J. (1980): SURVIVAL. A program package for the statistical analysis of censored survival times. Statistical Software Newsletter 6, 44-53
FINNEY, D.J. (1974): Problems, data, and Inference (with discussion). Journal of the Royal Statistical Society Series A 137, 1-22.
FISHER R.A. (1925): Statistical Methods for Research Workers. Oliver & Boyd, Edinburgh.
FREIDLIN, B,, MCSHANE, L. and KORN, E.L.(2010): Randomized Clinical Trials With Biomarkers: Design Issues. Journal National Cancer Institute 102, 152-160
KAUFMANN, M., PUSZTAI, L., RODY, A., CARDOSO, F., DIETEL, M., EDLER, l., HAHN, M., JONAT, W., KARN T., KREIPE. H., LOI, S., VON MINCKWITZ, G., SINN, H.P. and VAN DE VIJVER (2010/11): Use of standard markers and incorporation of molecular markers into breast cancer therapy (to appear).
LAURO, N.C. (1996): Computational statistics or statistical computing, is that the question? Computational Statistics and Data Analysis 23, 191-193.
L€UTER, J. (1981): Programmiersprache DIST. Dateneingabe und Datenstruktirierung. Akademie Verlag, Berlin.
LAGAKOS, S. W. and SCHOENFELD, D. A. (1984): Properties of proportional-hazards score tests under misspecified regression models. Biometrics 40,1037-1048.
NELDER, J. (1996): Statistical computing. In P. Armitage and D. Hand (Eds.): Advances in Biometry. 50 Years of the International Biometric Society. Wiley, New York, 201-212.
POTTER, M. (2005): A permutation test for inference in logistic regression with small- and moderate-sized data sets. Statistics in Medicine 24 (5), 693-708.
TSIATIS, A., ROSNER, G. L. and TRITCHLER, D. L. (1985): Group sequential tests with censored survival data adjusting for covariates. Biometrika 72(2), 365-373.
SARGENT, D.J., CONLEY, B.A., ALLEGRA, C., et al. (2005): Clinical trial designs for predictive marker validation in cancer treatment trials. Journal of Clinical Oncology 23(9), 2020-2027.
SCHÄFER, H. and MÜLLER, H. (2001): Modification of the sample size and the schedule of interim analyses in survival trials based on data inspections. Statistics in Medicine 20, 3741-3751.
SIMON, R. (2008). Using genomics in clinical trial design. Clinical Cancer Research 14, 5984-5993.
VICTOR, N. (1984): Computational statistics - science or tool? (with discussion). Statistical Software Newsletter 10, 105-125.
WUNDER, C., KOPP-SCHNEIDER, A, and EDLER, L. (2010): Adaptive group sequential trial to improve treatment in rare patient entities (to appear).
TUKEY, J.W. (1977): Exploratory Data Analysis. Addison-Wesley, New York.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Edler, L., Wunder, C., Werft, W., Benner, A. (2010). Computational Statistics Solutions for Molecular Biomedical Research: A Challenge and Chance for Both. In: Lechevallier, Y., Saporta, G. (eds) Proceedings of COMPSTAT'2010. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2604-3_2
Download citation
DOI: https://doi.org/10.1007/978-3-7908-2604-3_2
Published:
Publisher Name: Physica-Verlag HD
Print ISBN: 978-3-7908-2603-6
Online ISBN: 978-3-7908-2604-3
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)