Alle Professorinnen und Professoren

Prof. Dr. Ulrike Grömping

Publikationen

Grömping, U. (2018). prepplot: Prepare Figure Region for Base Graphics. R package version 0.7 (Manual, Vignette). In: R Development Core Team (2018). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. (2008-2018). The ic.infer Package (Inequality Constrained Inference in Linear Normal Situations). R package version 1.1-6. In: R Development Core Team (2018). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. and Fontana, R. (2018). An Algorithm for Generating Good Mixed Level Factorial Designs. Report 1/2018, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.

Grömping, U. (2018). Coding Invariance in Factorial Linear Models and a New Tool for Assessing Combinatorial Equivalence of Factorial Designs (Download Accepted Manuscript; eprint of published paper). Journal of Statistical Planning and Inference 193, 1-14. https://doi.org/10.1016/j.jspi.2017.07.004

Grömping, U. (2017). Data visualisation with R: 100 examples. Journal of Statistical Software 81, book review 2, 1-5.

Grömping, U. (2017-2018). DoE.MIParray: Creation of Arrays by Mixed Integer Programming. R package version 0.11. In: R Core Team (2017). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. (in press). R Package DoE.base for Factorial Designs. Journal of Statistical Software.

Grömping, U. (2009-2017). The DoE.wrapper Package (Wrapper package for design of experiments functionality). R package version 0.9. In: R Core Team (2017). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. (2017). Frequency tables for the coding invariant quality assessment of factorial designs. IISE Transactions 49, 505-517. http://www.tandfonline.com/doi/full/10.1080/0740817X.2016.1241458; download Accepted Manuscript, download free eprint of printed version.

Grömping, U. (2017). An Interaction-Based Decomposition of Generalized Word Counts Suited to Assessing Combinatorial Equivalence of Factorial Designs. Report 1/2017, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin. Further Examples.

Grömping, U. (2009-2018). The DoE.base Package (Full factorials, orthogonal arrays and base utilities for DoE packages). R package version 0.32. In: R Development Core Team (2017). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Vasilev, N., Boccard, J., Lang, G., Grömping, U., Fischer, R., Goepfert, S., Rudaz, S. and Schillberg, S. (2016). Structured plant metabolomics for the simultaneous exploration of multiple factors. Scientific Reports 6, Article number: 37390 (15 pages). doi:10.1038/srep37390. http://www.nature.com/articles/srep37390.

Grömping, U. (2016). Interaction Contributions as Coding Invariant Single Degree of Freedom Contributions to Generalized Word Counts. Report 2/2016, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin. (Report 1/2017 is an extended and refocussed version of this report; if you are not looking for something very specific from this report, I recommend to consult that new report.)

Grömping, U. (2007-2016). The FrF2 Package (Fractional Factorial designs with 2-level factors). R package version 1.7-2. In: R Development Core Team (2016). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. (2016). Practical Guide to Logistic Regression. Journal of Statistical Software 71, book review 3, 1-5.

Grömping, U. (2016). Corrigendum to Variable importance in regression models. WIREs Comput Stat 8(4), 154-157. (link to original article with corrected supporting information)

Grömping, U. and Bailey, R.A. (2016). Regular fractions of Factorial Arrays. In: Kunert, J., Müller, C. and Atkinson, A. (eds.), mODa 11 – Advances in Model-Oriented Design and Analysis, Springer International Publishing Switzerland, 143-151.

Grömping, U. (2016). R Package DoE.base for Factorial Designs. Report 1/2016, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.

Grömping, U. (2015). Using R and RStudio for Data Management, Statistical Analysis and Graphics (2nd Edition). Journal of Statistical Software 68, book review 4, 1-7.

Grömping, U. (2015). Augmented Half Normal Effects Plots in the Presence of a Few Error Degrees of Freedom. Quality and Reliability Engineering International 31(7), 1185-1196. Supplementary material.

Grömping, U. (2015). Variable importance in regression models. WIREs Comput Stat 7, 137-152. DOI: 10.1002/wics.1346. (Corrigendum, regarding the Fabbris metric and numeric results on the Green metric)

Grömping, U. (2015). Multilevel Modeling Using R. Journal of Statistical Software 62, book review 1, 1-6.

Vasilev, N., Schmitz, Ch., Grömping, U., Fischer, R. and Schillberg, S. (2014). Assessment of Cultivation Factors that Affect Biomass and Geraniol Production in Transgenic Tobacco Cell Suspension Cultures. PLoS ONE 9(8): e104620 (7 pages). DOI:10.1371/journal.pone.0104620.

Grömping, U. and Xu, H. (2014). Generalized resolution for orthogonal arrays. The Annals of Statistics 42(3), 918-939.

Grömping, U. (2014). Mosaic plots are useful for visualizing low order projections of factorial designs. The American Statistician 68(2), 108-116. DOI: 10.1080/00031305.2014.896829.
Download: accepted author version, supplementary material

Grömping, U. (2014). A Note on Dominating Fractional Factorial Two-Level Designs With Clear Two-Factor Interactions. Technometrics 56, 42-45. DOI: 10.1080/00401706.2013.822425.
Download: accepted author version, supplementary material

Grömping, U. (2014). R Package FrF2 for Creating and Analysing
Fractional Factorial 2-Level Designs. Journal of Statistical Software 56 (1), 1-56.

Grömping, U. (2013). Frequency tables for the coding invariant ranking of orthogonal arrays. Report 2/2013, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.

Grömping, U. and Xu, H. (2013). Generalized resolution for orthogonal arrays. Report 1/2013, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.

Vasilev, N., Grömping, U., Lipperts, A., Raven, N., Fischer, R. and Schillberg, S. (2013). Optimization of BY-2 cell suspension culture medium for the production of a human antibody using a combination of fractional factorial designs and the response surface method. Plant Biotechnology Journal 11(7), 867-874.

Grömping, U. (2009-2013). The RcmdrPlugin.DoE Package (R Commander Plugin for (industrial) Design of Experiments). R package version 0.12-2. In: R Development Core Team (2013). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. (2013). The R Primer. Journal of Statistical Software 52, book review 3, 1-5.

Grömping, U. (2012). Variable Importance Assessment in Regression: Linear Regression Versus the Random Forest. In:Vogt, W. P. and Johnson, R. B. (eds.) SAGE Benchmarks in Social Research Methods: Correlation and Regression Analysis (Vol I). Sage, Los Angeles.
(Reprint of Grömping 2009 American Statistician)

Grömping, U. (2012). Creating clear designs: a graph-based algorithm and a catalog of clear compromise plans. IIE Transactions 44, 988-1001. DOI:10.1080/0740817X.2012.654848.
Download: accepted author version, free eprint of printed version, supplementary material.

Grömping, U. (2010-2013). The FrF2.catlg128 Package (Catalogues of resolution IV 128 run 2-level fractional factorials up to 33 factors that do have 5-letter words). R package version 1.2-1. In: R Development Core Team (2012). R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria.

Grömping, U. (2011). Tutorial for designing experiments using the R package RcmdrPlugin.DoE. Report 4/2011, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.
Example data can be found here.

Grömping, U. (2011). Optimal Design of Experiments with R. Journal of Statistical Software 43, book review 5, 1-4.

Grömping, U. (2011). Industrial Design of Experiments in R. In: Melas, V., Nachtmann, G. and Rasch, D.: Optimal Design of Experiments -
Theory and Application: Proceedings of the International Conference
in Honor of the late Jagdish Srivastava. Center of Experimental Design
University of Natural Resources and Life Sciences, Vienna. ISBN 978-3-900962-96-8. pp 42-58.

Grömping, U. (2011). Relative projection frequency tables for orthogonal arrays. Report 1/2011, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.

Grömping, U. (2010). Design and Analysis of Experiments with SAS. Journal of Statistical Software 37, book review 2, 1-3.

Grömping, U. (2010). Creating clear designs: a graph-based algorithm and a catalogue of clear compromise plans. Report 5/2010, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin. (preprint of 2012 IIE Transactions article)

Grömping, U. (2010). "Clear" and "Distinct": two approaches for regular fractional factorial designs with estimability requirements. Report 2/2010, Reports in Mathematics, Physics and Chemistry, Department II, Beuth University of Applied Sciences Berlin.

Grömping, U. and Landau, S. (2010). Do not adjust coefficients in Shapley value regression. Applied Stochastic Models in Business and Industry 26, 194-202. Abstract: DOI: 10.1002/asmb.773. Final author version: PDF.

Grömping, U. (2010). Inference With Linear Equality And Inequality Constraints Using R: The Package ic.infer. Journal of Statistical Software 33, Issue 10, 1-31.

Grömping, U. (2009). Variable Importance Assessment in Regression: Linear Regression Versus Random Forest. The American Statistician 63, 308-319.
With supplemental files programs.zip and Supplement_shape.pdf.
Furthermore, on reader request, with a link to the Swiss dataset and a program for reading and preparing it.

Hautzinger, H., Grömping, U., Kreiß, J.-P., Mougeot, M., Pastor, C., Pfeiffer, M. and Zangmeister, T. (2008). Summary Report of Work Package 7 - Statistical Methods, Deliverable 7.5 for EU-Project TRaffic Accident Causation in Europe (Project No. 027763 – TRACE).

Grömping, U., Pfeiffer, M. and Stock, W. (2007). Statistical Methods for Improving the Usability of Existing Accident Databases. Deliverable 7.1 for EU-Project TRaffic Accident Causation in Europe (Project No. 027763 – TRACE).

Grömping, U. (2007). Response to comment by Scott Menard, re: Estimators of Relative Importance in Linear Regression Based on Variance Decomposition. In: Letters to the Editor, The American Statistician 61, 280-284.

Grömping, U. (2007). Estimators of Relative Importance in Linear Regression Based on Variance Decomposition. The American Statistician 61, 139-147.

Grömping, U. (2006). Relative Importance for Linear Regression in R: The Package relaimpo. Journal of Statistical Software 17, Issue 1.

Gerhorst, F., Grömping, U., Lloyd-Thomas, D., Khalaf, F. (2006): Design for Six Sigma in product development at Ford Motor Company in a case study on robust exhaust manifold design. Int. J. Product Development 3, 278-291.

Grömping, U., Menzler, S. and Weimann, U. (2005): Split-Register Study: A New Method for Estimating the Impact of Rare Exposure on Population Accident Risk based on Accident Register Data. In: BASt (2005, ed.): 1st International Conference on ESAR (Expert Symposium on Accident Research). Series "Berichte der Bundesanstalt für Straßenwesen", sub series "Fahrzeugtechnik", Report F55, 95-101.

Grömping, U. and Weimann, U. (2004). The asymptotic distribution of the partial attributable risk in cross-sectional studies. Statistics 38, 427-438.

Heinrichs, R. und Grömping, U. (2004). Customer Driven Diesel Vehicle Sound Quality. Proceedings of Internoise, PRAG 2004.

Heinrichs, R. und Grömping, U. (2003). Hauptdimension der Dieselgeräusch-Wahrnehmung. Proceedings of DAGA, Aachen 2003.

Grömping, U. and Weimann, U. (2003). A Statistical Method for Customer Satisfaction Inhibitor Estimation that Permits Calculation of Confidence Intervals. Ford Technical Journal, Vol. 6, No. 1 (January 2003, FTJ-2003-0007).

Grömping, U. and Weimann, U. (2002, with revision in 2003). The asymptotic distribution of the partial attributable risk in cross-sectional studies. More elaborate preprint of 2004 paper. Available on the Mathematics preprint server (link works after you have logged into the Mathematics preprint server). Download from here without login.

Grömping, U. and Bazant, C. (2002). Case Study "Seat Belt Retraction Time". Published on the ENBIS web site http://www.enbis.org/sig/design_of_experiments/docs/seat_belt_retraction_time (case studies accessible for ENBIS members only, membership free of charge).

Grömping, U. (2001). One-sided Likelihood Ratio Tests for Linear Inequalities on the Parameters of Normal Linear Models. In: Kunert, J. and Trenkler, G. (eds.): Mathematical Statistics with Applications in Biometry: Festschrift in Honour of Siegfried Schach. Eul, Köln.

Ziegler, A. und Grömping, U. (1998). The Generalised Estimating Equations: A Comparison of Procedures Available in Commercial Statistical Software Packages. Biometrical Journal 40, 245-260.

Grömping, U. (1996). Tests for a monotone dose-response relation in models with ordered categorical dose with emphasis on likelihood ratio tests for linear inequalities on normal means. PhD Thesis, Department of Statistics, Dortmund University, Germany.

Ziegler, A., Kastner, C., Grömping, U. und Blettner, M. (1996). The Generalized Estimating Equations in the Past Ten Years: An Overview and a Biomedical Application. Discussion Paper 24, Sonderforschungsbereich “Statistische Analyse diskreter Strukturen“ (SFB 386), Ludwig-Maximilians-University Munich, Germany.

Vach, W., Grömping, U., Schulz, K. (1996). On the relation between parameter estimates from transition and marginal models for longitudinal data. Research Report 28 at Freiburger Zentrum für Datenanalyse und Modellbildung, Albert-Ludwigs-University Freiburg, Germany. Postscript-File.

Grömping, U. (1996). A note on fitting a marginal model to mixed effects log-linear regression data via GEE. Biometrics 52, 280-285.

Ziegler, A., Kastner, C., Grömping, U. und Blettner, M. (1996). The Generalized Estimating Equations: Derivation and Applications (in German). Informatik, Biometrie und Epidemiologie in Medizin und Biologie 27, 69-91.

Barowski, M., Weimann, B., Grömping, U. und Schach, S. (1995). SAS. A course on the SAS-modules STAT, IML und GRAPH for advanced learners (in German). Script, Department of Statistics, Dortmund University, Germany.

Luttmann, H., Grömping, U., Kreienbrock, L., Treiber-Klötzer, C. und Wichmann, H.E. (1995). Kohortenstudie zu Atemwegserkrankungen und Lungenfunktion bei Schulkindern in Südwestdeutschland, Teil 4: Innerstädtische Umwelteinflüsse auf Atemwegserkrankungen in Mannheim. Zentralblatt für Hygiene und Umweltmedizin 198, 172-189.

Grömping, U. (1995). Subject-specific and population-averaged questions for log-linear regression data. In: Seeber, G.U.H. et al. (eds.): Statistical Modelling. Proceedings of the 10th International Workshop on Statistical Modelling, Innsbruck, Austria, 10-14 July, Springer, Heidelberg.

Grömping, U. (1994). Simple one- and two-sided likelihood ratio tests for multivariate normal means with applications as confirmatory trend tests. Research report No. 94/5, Department of Statistics, Dortmund University, Germany.

Grömping, U. (1993). GEE: A SAS Macro for Longitudinal Data Analysis (Version 2.0). Technical Report (Arbeitsbericht) 31, Department of Statistics, Dortmund University, Germany.

Luttmann, H., Grömping, U., Treiber-Klötzer, C. Kreienbrock, L., und Wichmann, H.E. (1993). Kohortenstudie zu Atemwegserkrankungen und Lungenfunktion bei Schulkindern in Südwestdeutschland, Teil 2: Regionale Einflüsse auf Atemwegserkrankungen in Mannheim und im Raum Freiburg. Zentralblatt für Hygiene und Umweltmedizin 196, 114-138.

Luttmann, H., Grömping, U., Kreienbrock, L., Treiber-Klötzer, C. und Wichmann, H.E. (1993). Kohortenstudie zu Atemwegserkrankungen und Lungenfunktion bei Schulkindern in Südwestdeutschland, Teil 1: Studiendesign, Prävalenz und Inzidenz von Atemwegserkrankungen. Zentralblatt für Hygiene und Umweltmedizin 194, 525-539.

Luttmann, H., Grömping, U., Wichmann, H.E., Kreienbrock, L. und Treiber-Klötzer, C. (1992). Auswirkungen der Luftverunreinigung auf die Gesundheit von Schulkindern. In: Van Eimeren, W., Überla, K., Ulm, K. (Hrsg.). Gesundheit und Umwelt. Medizinische Informatik, Biometrie und Epidemiologie 75, Springer, Berlin, 131-146.

Grömping, U. (1990). The EM Algorithm for Maximum-Likelihood-estimation in mixed linear models (in German). Diploma thesis, Department of Statistics, Dortmund University, Germany.

Grömping, U., Hennig, M., Kübler, J. und Schach, S. (1990). Introduction to the Statistical Analysis System (in German). Script, Department of Statistics, Dortmund University, Germany.