JProf. Dr. Sarah Friedrich

Group Head
Computational Statistics
http://orcid.org/0000-0003-0291-4378
Computational Statistics
Phone:
0551-39-64064Telefax:
0551-39-4995E-Mail:
Sarah.Friedrich@med.uni-goettingen.deOffice room:
Humboldtallee 32, GF 137ORCID iD:
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- Survival analysis
- Resampling- and permutation methods
- Causal models
- Semi- and nonparametrical statistics for dependent data
[Since 08/2019] | Assistant Professor at the Department of Medical Statistics, University Medical Center Göttingen |
[09/2018 - 05/2019] | Post-Doc, Section of Biostatistics, University of Kopenhagen |
[02/2015 - 08/2018] | Research associate with teaching and research activity, Institute of Statistics, Ulm University |
[09/2015] | Research visit at the University of Texas at Dallas |
[10/2012 - 09/2014] |
Studies of Mathematical Biometry at the Ulm University,
Degree: Master of Science (M.Sc.) |
Exam Thesis
- PhD (Dr. rer. nat.) at Ulm University (magna cum laude)
Dissertation title: ‘Permutation- and resampling-based inference for semi- and nonparametric effects in dependent data’ - Master’s Thesis: ’Estimation of pregnancy outcome probabilities in the presence of heavy left-truncation’
- Bachelor’s Thesis: ’Dataspectroscopy: Eigenspaces of convolution operators and clustering’
Publications
- Friedrich S, Antes G, Behr S, Binder H, Brannath W, Dumpert F, Ickstadt K, Kestler H, Lederer J, Leitgöb H, Pauly M, Steland A, Wilhelm A, Friede T (2020) Is there a role for statistics in artificial intelligence? [Preprint]
- Meaidi A, Friedrich S, Lidegaard Ø (2020) Risk of surgical evacuation and risk of major surgery following second-trimester medical abortion in Denmark: A nationwide cohort study Contraception. 102: 201-206. [Full text]
- Friedrich, S, Friede, T (2020) Causal inference methods for small non-randomized studies: Methods and an application in COVID-19. [Preprint]
- Voormolen DC, Zeldovich M, Haagsma JA, Polinder S, Friedrich S, Maas AI, Wilson L, Steyerberg EW, Covic A, Andelic N, Plass AM, Wu YJ, Asendorf T, von Steinbüechel N (2020) Outcomes after Complicated and Uncomplicated Mild Traumatic Brain Injury at Three-and Six-Months Post-Injury: Results from the CENTER-TBI Study. Journal of Clinical Medicine 9: 1525. [Open Access]
- Ditzhaus M, Friedrich S (2020) More powerful logrank permutation tests for two-sample survival data. Journal of Statistical Computation and Simulation 90: 2209-2227. [Full text]
- Friedrich S, Konietschke F, Pauly M (2019) Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM. The R Journal 11: 380-400. [Open Access]
- Knoll, A, Pala, A, Pedro, M-T, Bäzner, U, König, R, Wirtz, C, Friedrich, S, Pauly, M and Antoniadis, G (2019). Clinical outcome after decompression of intraneural peroneal ganglion cyst and its morphologic correlation to postoperative nerve ultrasound. Journal of Neurosurgery, 1, 1–7, doi: 10.3171/2019.3.JNS182699.
- Meaidi, A, Friedrich, S, Gerds, TA and Lidegaard, O (2019). Risk factors for surgical intervention of early medical abortion. American Journal of Obstetrics and Gynecology, 220(5), 478.e1-478.e15, doi: 10.1016/j.ajog.2019.02.014.
- Ditzhaus, M and Friedrich, S (2018). More powerful logrank permutation tests for two-sample survival data. arXiv-Preprint arXiv:1807.05504. Submitted to Journal of Statistical Computation and Simulation.
- Friedrich, S, Konietschke, F and Pauly, M (2018). Analysis of Multivariate Data and Repeated Measures Designs with the R Package MANOVA.RM. arXiv-Preprint arXiv:1801.08002. MANOVA in meaningful effects. Annals of the Institute of Statistical Mathematics, doi: 10.1007/s10463-019-00717-3.
- Bathke, A, Friedrich, S, Konietschke, F, Pauly, M, Staffen, W, Strobl, N and Höller, Y (2018). Testing Mean Differences among Groups: Multivariate and Repeated Measures Analysis with Minimal Assumptions. Multivariate Behavioral Research, 53(3), 348–359.
- Friedrich, S and Pauly, M (2018). MATS: Inference for potentially Singular and Heteroscedastic MANOVA. Journal of Multivariate Analysis, 165, 166–179
- Friedrich, S, Konietschke, F and Pauly, M (2017). A Wild Bootstrap Approach for Nonparametric Repeated Measurements. Computational Statistics and Data Analysis, 113, 38–52
- Friedrich, S, Konietschke, F and Pauly, M (2017). GFD: An R-package for the Analysis of General Factorial Designs. Journal of Statistical Software, 79(1), 1–18.
- Friedrich, S, Brunner, E and Pauly, M (2017). Permuting Longitudinal Data In Spite Of The Dependencies. Journal of Multivariate Analysis, 153, 255–265
- Friedrich, S, Beyersmann, J, Winterfeld, U, Schumacher, M and Allignol, A (2017). Nonparametric Estimation of Pregnancy Outcome Probabilities. Annals of Applied Statistics, 11(2), 840–867, doi: 10.1214/17-AOAS1020.
R-Packages
- GFD: Tests for General Factorial Designs
- rankFD: Rank-Based Tests for General Factorial Designs
- MANOVA.RM: Analysis of Multivariate Data and Repeated Measures Designs
- rankMANOVA: Rank-Based Tests for Multivariate Data in Nonparametric Factorial Designs
- mdir.logrank: Multiple-direction logrank test