Research Report for the year 1980-2014

Scientific publications

Journal Articles:
  • Bauer R, Gottfriedsen G-U, Binder H, Dobmeier M, Cording C, Hajak G, Spiessl H: Burden of caregivers of patients with bipolar affective disorders. Am J Orthopsychiat, 2011; 81: 139-148. : http://dx.doi.org/10.1111/j.1939-0025.2010.01081.x
  • Binder H, Allignol A, Schumacher M, Beyersmann J: Boosting for high-dimensional time-to-event data with competing risks. Bioinformatics, 2009; 25: 890-896. : http://dx.doi.org/10.1093/bioinformatics/btp088
  • Binder H, Benner A, Bullinger L, Schumacher M: Tailoring sparse multivariable regression techniques for prognostic single-nucleotide polymorphism signatures. Stat Med, 2013; 32: 1778-1791. : http://dx.doi.org/10.1002/sim.5490
  • Binder H, Müller T, Schwender H, Golka K, Steffens M, Hengstler JG, Ickstadt K, Schumacher M: Cluster-Localized Sparse Logistic Regression for SNP Data. Stat Appl Genet Mol, 2012; 11 (online). : http://dx.doi.org/10.1515/1544-6115.1694
  • Binder H, Porzelius C, Schumacher M: An overview of techniques for linking high-dimensional molecular data to time-to-event endpoints by risk prediction models. Biometrical J, 2011; 53: 170-189. : http://dx.doi.org/10.1002/bimj.201000152
  • Binder H, Sauerbrei W: Increasing the usefulness of additive spline models by knot removal. Comput Stat Data An, 2008; 52: 5305-5318. : http://dx.doi.org/10.1016/j.csda.2008.05.009
  • Binder H, Sauerbrei W: Stability analysis of an additive spline model for respiratory health data by using knot removal. J R Stat Soc C-appl, 2009; 58: 577-600. : http://dx.doi.org/10.1111/j.1467-9876.2009.00668.x
  • Binder H, Sauerbrei W: Adding local components to global functions for continuous covariates in multivariable regression modeling. Stat Med, 2010; 29: 800-817. : http://dx.doi.org/10.1002/sim.3739
  • Binder H, Sauerbrei W, Royston P: Comparison between splines and fractional polynomials for multivariable model building with continuous covariates: a simulation study with continuous response. Stat Med, 2013; 32: 2262-2277. : http://dx.doi.org/10.1002/sim.5639
  • Binder H, Schumacher M: Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models. Bmc Bioinformatics, 2008; 9: 10-19.
  • Binder H, Schumacher M: Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples. Statistical Applications in Genetics and Molecular Biology, 2008; 7 (1) (online): Article 12. : http://www.bepress.com/sagmb/vol7/iss1/art12
  • Binder H, Schumacher M: Comment on ‘network-constrained regularization and variable selection for analysis of genomic data’. Bioinformatics, 2008; 24: 2566-2568. : http://dx.doi.org/10.1093/bioinformatics/btn412
  • Binder H, Schumacher M: Incorporating pathway information into boosting estimation of high-dimensional risk prediction models. Bmc Bioinformatics, 2009; 10 (1) (online): 18. : http://dx.doi.org/10.1186/1471-2105-10-18
  • Binder H, Tutz G: A comparison of methods for the ļ¬tting of generalized additive models. Stat Comput, 2008; 18: 87-99.
  • Gade S, Porzelius C, Faelth M, Brase JC, Wuttig D, Kuner R, Binder H, Sueltmann H, Beissbarth T: Graph based fusion of miRNA and mRNA expression data improves clinical outcome prediction in prostate cancer. Bmc Bioinformatics, 2011; 12 (online): 488. : http://dx.doi.org/10.1186/1471-2105-12-488
  • Hieke S, Binder H, Nieters A, Schumacher M: minPtest: a resampling based gene region-level testing procedure for genetic case-control studies. Computation Stat, 2014; 29: 51-63. : http://dx.doi.org/10.1007/s00180-012-0391-4
  • Knaus J, Hieke S, Binder H, Schwarzer G: Costs of Cloud Computing for a Biometry Department. A Case Study. Method Inform Med, 2013; 52: 72-79. : http://dx.doi.org/10.3414/ME11-02-0048
  • Knaus J, Porzelius C, Binder H, Schwarzer G: Easier Parallel Computing in R with snowfall and sfCluster. The R Journal, 2009; 1: 54-59.
  • Landgrebe M, Binder H, Koller M, Eberl Y, Kleinjung T, Eichhammer P, Graf E, Hajak G, Langguth B: Design of a placebo-controlled, randomized study of the efficacy of repetitive transcranial magnetic stimulation for the treatment of chronic tinntius. BMC Psychiatry, 2008; 8: 1-9. : http://www.biomedcentral.com/1471-244X/8/23; doi:10.1186/1471-244X-8-23
  • Langguth B, Bauer E, Feix S, Landgrebe M, Binder H, Sand P, Hajak G, Eichhammer P: Modulation of human motor cortex excitability by the cholinesterase inhibitor rivastigmine. Neurosci Lett, 2007; 415: 40-44.
  • Langguth B, Eichhammer P, Zowe M, Landgrebe M, Binder H, Sand P, Hajak G: Modulating cerebello-thalamocortical pathways by neuronavigated cerebellar repetitive transcranial stimulation (rTMS). Clin Neurophysiol, 2008; 38: 289-295.
  • Langguth B, Kleinjung T, Marienhagen J, Binder H, Sand PG, Hajak G, Eichhammer P: Transcranial magnetic stimulation for the treatment of tinnitus: effects on cortical excitability. Bmc Neurosci, 2007; 8 (online).
  • Nührenberg TG, Langwieser N, Binder H, Kurz T, Stratz C, Kienzle R-P, Trenk D, Zohlnhöfer-Momm D, Neumann F-J: Transcriptome analysis in patients with progressive coronary artery disease: identification of differential gene expression in peripheral blood. J Cardiovasc Transl, 2013; 6: 81-93. : http://dx.doi.org/10.1007/s12265-012-9420-5
  • Porzelius C, Binder H, Schumacher M: Parallelized prediction error estimation for evaluation of high-dimensional models. Bioinformatics, 2009; 25: 827-829. : http://dx.doi.org/10.1093/bioinformatics/btp062
  • Porzelius C, Johannes M, Binder H, BeißbarthT: Leveraging external knowledge on molecular interactions in classification methods for risk prediction of patients. Biometrical J, 2011; 53: 190-201. : http://dx.doi.org/10.1002/bimj.201000155
  • Porzelius C, Schumacher M, Binder H: A general, prediction error-based criterion for selecting model complexity for high-dimensional survival models. Stat Med, 2010; 29: 830-838. : http://dx.doi.org/10.1002/sim.3765
  • Porzelius C, Schumacher M, Binder H: Sparse regression techniques in low-dimensional survival data settings. Stat Comput, 2010; 20: 151-163. : http://dx.doi.org/10.1007/s11222-009-9155-6
  • Porzelius C, Schumacher M, Binder H: The benefit of data-based model complexity selection via prediction error curves in time-to-event data. Computation Stat, 2011; 26: 293-302. : http://dx.doi.org/10.1007/s00180-011-0236-6
  • Reiser V, Porzelius C, Stampf S, Schumacher M, Binder H: Can matching improve the performance of boosting for identifying important genes in observational studies? Computation Stat, 2013; 28: 37-49. (download: http://dx.doi.org/10.1007/s00180-012-0306-4)
  • Rücker G, Reiser V, Motschall E, Binder H, Meerpohl JJ, Antes G, Schumacher M: Boosting qualifies capture–recapture methods for estimating the comprehensiveness of literature searches for systematic reviews. J Clin Epidemiol, 2011; 64: 1364-1372. : http://dx.doi.org/10.1016/j.jclinepi.2011.03.008
  • Rücker G, Schwarzer G, Carpenter JR, Binder H, Schumacher M: Treatment-effect estimates adjusted for small-study effects via a limit meta-analysis. Biostatistics, 2011; 12: 122-142. : http://dx.doi.org/10.1093/biostatistics/kxq046
  • Sariyar M, Schumacher M, Binder H: A boosting approach for adapting the sparsity of risk prediction signatures based on different molecular levels. Stat Appl Genet Mol, 2014; 13: 343-357. : http://dx.doi.org/10.1515/sagmb-2013-0050
  • Sauerbrei W, Boulesteix A-L, Binder H: Stability investigations of multivariable regression models derived from low- and high-dimensional data. J Biopharm Stat, 2011; 21: 1206-1231. (download: http://dx.doi.org/10.1080/10543406.2011.629890)
  • Sauerbrei W, Royston P, Binder H: Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat Med, 2007; 26: 5512-5528.
  • Schoop R, Beyersmann J, Schumacher M, Binder H: Quantifying the predictive accuracy of time-to-event models in the presence of competing risks. Biometrical J, 2011; 53: 88-112. : http://dx.doi.org/10.1002/bimj.201000073
  • Schumacher M, Binder H, Gerds T: Assessment of survival prediction models based on microarray data. Bioinformatics, 2007; 23: 1768-1774.
  • Singer S, Meyer A, Wienholz S, Briest S, Brown A, Dietz A, Binder H, Jonas S, Papsdorf K, Stolzenburg JU, Kohler U, Rassler J, Zwerenz R, Schroter K, Mehnert A, Lobner M, Konig HH, Riedel-Heller SG: Early retirement in cancer patients with or without comorbid mental health conditions: a prospective cohort study. Cancer-am Cancer Soc, 2014; 120 (14): 2199-2206. : http://dx.doi.org/10.1002/cncr.28716
  • Spießl A, Binder H, Cording C, Klein HE, Spießl H: Patients with mental retardation in a psychiatric hospital. Psychiat Prax, 2008; 35: 67-72.
  • Sreseli RT, Binder H, Kuhn M, Digel W, Veelken H, Sienel W, Passlick B, Schumacher M, Martens UM, Zimmermann S: Identification of a 17-protein signature in the serum of lung cancer patients. Oncol Rep, 2010; 24: 263-270.
  • Stratz C, Nührenberg T, Fiebich BL, Amann M, Kumar A, Binder H, Hoffmann I, Valina C, Hochholzer W, Trenk D, Neumann F-J: Controlled type II diabetes mellitus has no major influence on platelet micro-RNA expression Results from micro-array profiling in a cohort of 60 patients. Thromb Haemostasis, 2014; 111: 902-911. : http://dx.doi.org/10.1160/TH13-06-0476
  • Stratz C, Nührenberg TG, Binder H, Valina CM, Trenk D, Hochholzer W, Neumann FJ, Fiebich BL: Micro-array profiling exhibits remarkable intra-individual stability of human platelet micro-RNA. Thromb Haemostasis, 2012; 107: 634-641. : http://dx.doi.org/10.1160/TH11-10-0742
  • Tutz G, Binder H: Boosting ridge regression. Comput Stat Data An, 2007; 51: 6044-6059.
Book Chapters:
  • Binder H, Graf E: Brier scores. In: Kattan, M. W. (Hrsg.): Encyclopedia of Medical Decision Making. SAGE Publications, 2009.
  • Schumacher M, Holländer N, Schwarzer G, Binder H, Sauerbrei W: Prognostic Factor Studies. In: Crowley J, Hoering A (Hrsg.): Handbook of Statistics in Clinical Oncology, Third Edition. Chapman and Hall/CRC, 2012; 415-470.