Methodische Forschung

2021

• Wallisch C., Dunkler D., Rauch G., de Bin R., Heinze G.:
  Selection of variables for multivariable models: Opportunities and limitations in quantifying model stability by resampling.
  Stat Med. 2021;40(2):369-381.
  PMC7820988
• Pilz M., Kunzmann K., Herrmann C., Rauch G., Kieser M.:
  Optimal planning of adaptive two-stage designs.
  Stat Med. 2021;40(13):3196-3213.
• Kruppa J., Sieg M., Richter G., Pohrt A.:
  Estimands in epigenome-wide association studies.
  Clin Epigenetics. 2021;13(1):98.
  PMC8086103
• Konietschke F., Schwab K., Pauly M.:
  Small sample sizes: A big data problem in high-dimensional data analysis.
  Stat Methods Med Res. 2021;30(3):687-701.
  PMC8008424
• Herrmann C., Rauch G.:
  Smoothing Corrections for Improving Sample Size Recalculation Rules in Adaptive Group Sequential Study Designs.
  Method Inform Med. 2021;epub:1-6.
• Cui Y., Konietschke F., Harrar S.W.:
  The nonparametric Behrens-Fisher problem in partially complete clustered data.
  Biometrical J. 2021;63(1):148-167.
• Becher H., Aigner A.:
  Methods to estimate proportion and number of nonexposed cases in a population.
  Biometrical J. 2021;63(3):514-527.

2020

• Zonneveld T.P., Aigner A., Groenwold R.H.H., Algra A., Nederkoorn P.J., Grittner U., Kruyt N.D., Siegerink B.:
  Confounding adjustment performance of ordinal analysis methods in stroke studies.
  PLoS ONE. 2020;15(4):e0231670.
  PMC7162480
• Noguchi K., Abel R.S., Marmolejo-Ramos F., Konietschke F.:
  Nonparametric multiple comparisons.
  Behav Res Methods. 2020;52(2):489-502.
• Li X., Herrmann C., Rauch G.:
  Optimality criteria for futility stopping boundaries for group sequential designs with a continuous endpoint.
  BMC Med Res Methodol. 2020;20(1):274.
  PMC7643306
• Herrmann C., Pilz M., Kieser M., Rauch G.:
  A new conditional performance score for the evaluation of adaptive group sequential designs with sample size recalculation.
  Stat Med. 2020;39(15):2067-2100.
• Bach P., Wallisch C., Klein N., Hafermann L., Sauerbrei W., Steyerberg E.W., Heinze G., Rauch G., for topic group 2 of the STRATOS initiative:
  Systematic review of education and practical guidance on regression modeling for medical researchers who lack a strong statistical background: Study protocol.
  PLoS ONE. 2020;15(12):e0241427.
  PMC7751867

2019

• Roy A., Harrar S.W., Konietschke F.:
  The nonparametric Behrens-Fisher problem with dependent replicates.
  Stat Med. 2019;38(25):4939-4962.
• Piper S.K., Grittner U., Rex A., Riedel N., Fischer F., Nadon R., Siegerink B., Dirnagl U.:
  Exact replication: Foundation of science or game of chance?
  PLoS Biol. 2019;17(4):e3000188.
  PMC6456162
• Pilz M., Kunzmann K., Herrmann C., Rauch G., Kieser M.:
  A variational approach to optimal two-stage designs.
  Stat Med. 2019;38(21):4159-4171.
• Ozga A.K., Rauch G.:
  Introducing a new estimator and test for the weighted all-cause hazard ratio.
  BMC Med Res Methodol. 2019;19(1):118.
  PMC6560733
• Konietschke F., Friede T., Pauly M.:
  Semi-parametric analysis of overdispersed count and metric data with varying follow-up times: Asymptotic theory and small sample approximations.
  Biometrical J. 2019;61(3):616-629.
  PMC6587510
• li>Feißt M., Hennigs A., Heil J., Moosbrugger H., Kelava A., Stolpner I., Kieser M., Rauch G.:
  Refining scores based on patient reported outcomes - statistical and medical perspectives.
  BMC Med Res Methodol. 2019;19(1):167.
  PMC6670170
• Feißt M., Heil J., Stolpner I., von Au A., Domschke C., Sohn C., Kieser M., Rauch G., Hennigs A.:
  Psychometric validation of the Breast Cancer Treatment Outcome Scale (BCTOS-12): a prospective cohort study.
  Arch Gynecol Obstet. 2019;300(6):1679-1686.
• Amro L., Konietschke F., Pauly M.:
  Multiplication-combination tests for incomplete paired data.
  Stat Med. 2019;38(17):3243-3255.

2018

• Ozga A.K., Kieser M., Rauch G.:
  A systematic comparison of recurrent event models for application to composite endpoints.
  BMC Med Res Methodol. 2018;18(1):2.
  PMC5755224
• Rauch G., Brannath W., Brückner M., Kieser M.:
  The Average Hazard Ratio - A Good Effect Measure for Time-to-event Endpoints when the Proportional Hazard Assumption is Violated?
  Method Inform Med. 2018;57(3):89-100.
• Rauch G., Kieser M., Binder H., Bayes-Genis A., Jahn-Eimermacher A.:
  Time-to-first-event versus recurrent-event analysis: points to consider for selecting a meaningful analysis strategy in clinical trials with composite endpoints.
  Clin Res Cardiol. 2018;107(5):437-443.
• Rauch G., Kunzmann K., Kieser M., Wegscheider K., König J., Eulenburg C.:
  A weighted combined effect measure for the analysis of a composite time-to-first-event endpoint with components of different clinical relevance.
  Stat Med. 2018;37(5):749-767.

2017

• Kieser M., Wirths M., Englert S., U.Kunz C., Rauch G.:
  OneArmPhaseTwoStudy: an R package for planning, conducting, and analysing single-arm phase II studies
  J Stat Softw. 2017;81(8):1-28.
• Schüler S., Kieser M., Rauch G.:
  Choice of futility boundaries for group sequential designs with two endpoints.
  BMC Med Res Methodol. 2017;17(1):119.
  PMC5549398
• Neumann K., Grittner U., Piper S.K., Rex A., Florez-Vargas O., Karystianis G., Schneider A., Wellwood I., Siegerink B., Ioannidis J.P.A., Kimmelman J., Dirnagl U.:
  Increasing efficiency of preclinical research by group sequential designs.
  PLoS Biol. 2017;15(3):e2001307.
  PMC5345756
• Sander A., Rauch G., Kieser M.:
  Blinded sample size recalculation in clinical trials with binary composite endpoints.
  J Biopharm Stat. 2017;27(4):705-715.

2016

• Rauch G., Schüler S., Wirths M., Englert S., Kieser M.:
  Adaptive Designs for two Candidate Primary Time-to-Event Endpoints
  Stat Biopharm Res. 2016;8:207-216.

2015

• Rauch G., Kieser M.:
  Adaptive designs for clinical trials with multiple endpoints
  Clin Investig. 2015;5:433-435.
• Kieser M., Rauch G.:
  Two-stage designs for cross-over bioequivalence trials.
  Stat Med. 2015;34(16):2403-16.
• Kieser M., Englert S., Rauch G.:
  Adaptive designs for phase II oncology trials
  Clin Investig. 2015;5:363-366.
• Rauch G., Rauch B., Schüler S., Kieser M.:
  Opportunities and challenges of clinical trials in cardiology using composite primary endpoints.
  World J Cardiol. 2015;7(1):1-5.
  PMC4306200

2014

• Rauch G., Wirths M., Kieser M.:
  Consistency-adjusted alpha allocation methods for a time-to-event analysis of composite endpoints
  Comput Stat Data An. 2014;75:151-161.
• Rauch G., Kieser M., Ulrich S., Doherty P., Rauch B., Schneider S., Riemer T., Senges J.:
  Competing time-to-event endpoints in cardiology trials: a simulation study to illustrate the importance of an adequate statistical analysis.
  Eur J Prev Cardiol. 2014;21(1):74-80.
• Rauch G., Jahn-Eimermacher A., Brannath W., Kieser M.:
  Opportunities and challenges of combined effect measures based on prioritized outcomes.
  Stat Med. 2014;33(7):1104-20.
• Schüler S., Mucha A., Doherty P., Kieser M., Rauch G.:
  Easily applicable multiple testing procedures to improve the interpretation of clinical trials with composite endpoints.
  Int J Cardiol. 2014;175(1):126-32.

2013

• Rauch G., Kieser M.:
  An expected power approach for the assessment of composite endpoints and its components.
  Comput Stat Data An. 2013;60:111-122.
• Rauch G., Beyersmann J.:
  Planning and evaluating clinical trials with composite time-to-first event endpoints in a competing risk framework
  Stat Med. 2013;32:3595-3608.