Submitted statistical articles

41 Erdmann, A., Beyersmann, J., Rufibach, K. (2023+). Oncology clinical trial design planning based on a multistate model that jointly models progression-free and overall survival endpoints. Submitted. arxiv | github | R package on cran | linkedin |
40 Polito, L., Liang, Q., Pal, N., Mpofu, P., Sawas, A., Humblet, O. Rufibach, K., Heinzmann, D. (2023+). Applying the Estimand and Target Trial frameworks to external control analyses using observational data: a case study in the solid tumor setting. Submitted. arxiv |

Articles in statistical journals

39 Rufibach, K., Grinsted, L., Li, J., Weber, H.-J., Zheng, C. Zhou, J. (2023). Quantification of follow-up time in oncology clinical trials with a time-to-event endpoint: Asking the right questions. Pharmaceutical Statistics, 22(4), 671-691. doi | arxiv | markdown |
38 Rufibach, K., Stegherr, R., Schmoor, C., Jehl, V., Allignol, A., Boeckenhoff, A., Dunger-Baldauf, C., Eisele, L., Künzel, T., Kupas, K., Leverkus, F., Trampisch, M., Zhao, Y., Friede, Beyersmann, J. (2023). Survival analysis for AdVerse events with VarYing follow-up times (SAVVY) – comparison of adverse event risks in randomized controlled trials. Statistics in Biopharmaceutical Research, to appear. doi | arxiv | markdown | podcast | . The first two authors contributed equally.
37 Ionan, A.C., Paterniti, M., Mehrotra, D., Scott, J., Ratitch, B., Collins, S., Gomatam, S., Nie, L., Rufibach, K., Bretz, F. (2023). Clinical and Statistical Perspectives on the Estimand Framework Implementation. Statistics in Biopharmaceutical Research, 15(3), 554-559. doi |
36 Rajeshwari, S., Barksdale, E., Marchenko, O., Jiang, Q., Ando, Y., Bloomquist, E., Coory, M., Crouse, M., Degtyarev, E., Framke, T., Freidlin, B., Gerber, D.E., Gwise, T., Josephson, F., Hess, L., Kluetz, P., Li, D., Mandrekar, S., Posch, M., Rantell, K., Ratitch, B., Raven, A., Roes, K., Rufibach, K., Sarac, S.B., Simon, R., Singh, H., Theoret, M., Thomson, A., Zuber, E., Shen, Y.L., Pazdur, R. (2023). Cancer Clinical Trials Beyond Pandemic: Report of an American Statistical Association Biopharmaceutical Section Open Forum Discussion. Statistics in Biopharmaceutical Research, 15(2), 444-449. doi |
35 Collignon, O., Schiel, A., Burman, C.F., Rufibach, K., Posch, M., Bretz, F. (2022). Estimands and Complex Innovative Designs. Clinical Pharmacology & Therapeutics, 112(6), 118-1190. doi |
34 Kunzmann, K, Grayling, M.J., Lee, K.M., Robertson, D.S., Rufibach, K., Wason, J.M.S. (2022). Conditional Power and Friends: The Why and How of (Un)planned, Unblinded Sample Size Recalculations in Confirmatory Trials. Stat. Med., 41(5), 877-890. doi | arxiv |
33 Manitz, J., Kan-Dobrosky, N., Buchner, H., Casadebaig, M.L., Haddad, V., Jie, F., Martin, E., Tang, R., Yung, G., Zhou, J., Stalbovskaya, V., Shentu, Y., Rufibach, K., Mo, M., Dey, J., Degtyarev, E. (2022). Estimands for Overall Survival in Clinical Trials with Treatment Switching in Oncology. Pharm. Stat., 21(NA), 150-162. doi |
32 Stegherr, R., Schmoor, C., Beyersmann, J., Rufibach, K., Jehl, V., Brueckner, A., Eisele, L., Kuenzel, T., Kupas, K., Langer, F., Loos, A., Norenberg, C., Voss, F., Friede, T. (2021). Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): Estimation of adverse event risks. Trials, 22(1), 420. doi | arxiv | markdown | podcast |
31 Kunzmann, K, Grayling, M.J., Lee, K.M., Robertson, D.S., Rufibach, K., Wason, J.M.S. (2021). A review of Bayesian perspectives on sample size derivation for confirmatory trials. Am. Stat., 75(4), 424-432. doi | arxiv | github | shiny |
30 Bornkamp, B., Rufibach, K., Lin, J., Liu, Y., Mehrotra, D., Roychoudhury, S., Schmidli, H., Shentu, Y., Wolbers, M. (2021). Principal Stratum Strategy: Potential Role in Drug Development. Pharm. Stat., 20(NA), 737-751. doi | arxiv | markdown |
29 Sun, S., Weber, J., Butler, E., Rufibach, K., Roychoudhury, S. (2021). Estimands in Hematology Trials. Pharm. Stat., 20(NA), 793-805. doi | arxiv |
28 Stegherr, R., Beyersmann, J., Jehl, V., Rufibach, K., Leverkus, F., Schmoor, C., Friede, T. (2021). Survival analysis for AdVerse events with VarYing follow-up times (SAVVY): Rationale and statistical concept of a meta-analytic study. Biom. J., 63(NA), 650-670. doi | arxiv | markdown | podcast |
27 Lawrence, R., Degtyarev, E., Griffiths, P., Trask, P., Lau, H., D’Alessio, D., Griebsch, I., Wallenstein, G., Cocks, K., Rufibach, K. (2020). What is an estimand and how does it relate to quantifying the effect of treatment on patient-reported quality of life outcomes in clinical trials. J Patient Rep Outcomes, 4(68), NA. doi |
26 Degtyarev, E., Rufibach, K., Shentu, Y., Yung, G., Casey, M., Englert, S., Liu, F., Liu, Y., Sailer, O., Siegel, J., Sun, S., Tang, R. (2020). Assessing the impact of COVID-19 on the objective and analysis of oncology clinical trials - application of the estimand framework. Statistics in Biopharmaceutical Research, 12(4), 427-437. doi | arxiv | . The first four authors contributed equally.
25 Rufibach, K., Heinzmann, D., Monnet, A. (2020). Integrating Phase 2 into Phase 3 based on an Intermediate Endpoint While Accounting for a Cure Proportion - with an Application to the Design of a Clinical Trial in Acute Myeloid Leukemia. Pharm. Stat., 19(NA), 44-58. doi | arxiv | github |
24 Beyer, U., Dejardin, D., Meller, M., Rufibach, K., Burger, H.U. (2019). A multistate model for early decision making in oncology. Biom. J., 62(3), 550-567. doi | arxiv |
23 Meller, M., Beyersmann, J., Rufibach, K. (2019). Joint modelling of progression-free and overall survival and computation of correlation measures. Stat. Med., 38(NA), 4270-4289. doi | arxiv |
22 Rufibach, K. (2019). Treatment Effect Quantification for Time-to-event Endpoints - Estimands, Analysis Strategies, and beyond. Pharm. Stat., 18(NA), 144-164. doi | arxiv |
21 Rufibach, K., Burger, H.U., Abt, M. (2016). Bayesian Predictive Power: Choice of Prior and some Recommendations for its Use as Probability of Success in Drug Development. Pharm. Stat., 15(NA), 438-446. doi | github | R package on cran |
20 Asikanius, E., Rufibach, K., Bahlo, J., Bieska, G., Burger, H.U. (2016). Comparison of design strategies for a three-arm clinical trial with time-to-event endpoint. Biom. J., 58(6), 1295-1310. doi |
19 Rufibach, K., Chen M., Ngyuen, H. (2016). Comparison of different clinical development plans for confirmatory subpopulation selection. Contemp. Clin. Trials, 47(NA), 78-84. doi |
18 Rufibach, K., Jordan, P., Abt, M. (2016). Sequentially Updating the Likelihood of Success of a Phase 3 Pivotal Time-To-Event Trial based on Interim Analyses or External Information. J. Biopharm. Stat., 26(2), 191-201. doi | R package on cran |
17 Dümbgen, L., Rufibach, K., Schuhmacher, D. (2014). Maximum-Likelihood Estimation of a Log-Concave Density based on Censored Data. Electron. J. Stat., 8(NA), 1405-1437. doi | arxiv | R package on cran |
16 Balabdaoui, F., Jankowski, H., Rufibach, K., Pavlides, M. (2013). Asymptotics of the discrete log-concave maximum likelihood estimator and related applications. J. R. Stat. Soc. Ser. B Stat. Methodol., 75(4), 769-790. doi | arxiv | R package on cran |
15 Rufibach, K. (2012). A smooth ROC curve estimator based on log-concave density estimates. Int. J. Biostat., 8(1), 1-29. doi | arxiv | R package on cran |
14 Rufibach, K. (2011). Selection models with monotone weight functions in meta analysis. Biom. J., 53(4), 689-704. doi | arxiv | R package on cran |
13 Dümbgen, L., Rufibach, K. (2011). logcondens: Computations Related to Univariate Log-Concave Density Estimation. Journal of Statistical Software, 39(6), 1-28. doi | R package on cran |
12 Held, L., Rufibach, K., Balabdaoui, F. (2010). A score regression approach to assess calibration of probabilistic predictions. Biometrics, 66(4), 1295-1305. doi |
11 Balabdaoui, F., Rufibach, K., Santambrogio, F. (2010). Least Squares estimation of two ordered monotone regression curves. J. Nonparametr. Stat., 22(8), 1019-1037. doi | arxiv | R package on cran |
10 Rufibach, K., Walther, G. (2010). The block criterion for multiscale inference about a density with applications to other multiscale problems. J. Comput. Graph. Statist., 19(1), 175-190. doi | R package on cran |
9 Rufibach, K. (2010). An Active Set Algorithm to Estimate Parameters in Generalized Linear Models with Ordered Predictors. Comput. Statist. Data Anal., 54(NA), 1442-1456. doi | arxiv | R package on cran |
8 Rufibach, K. (2009). reporttools: R Functions to Generate LaTeX Tables of Descriptive Statistics. Journal of Statistical Software, Code Snippets, 31(1), NA. doi | R package on cran |
7 Müller, S., Rufibach, K. (2009). Smooth tail index estimation. J. Statist. Comput. Simulation, 79(NA), 1155-1167. doi | arxiv | R package on cran |
6 Balabdaoui, F., Rufibach, K., Wellner, J.A. (2009). Limit distribution theory for maximum likelihood estimation of a log-concave density. Ann. Statist., 37(NA), 1299-1331. doi | arxiv | R package on cran |
5 Dümbgen, L., Rufibach, K. (2009). Maximum likelihood estimation of a log-concave density and its distribution function: basic properties and uniform consistency. Bernoulli, 15(NA), 40-68. doi | arxiv | R package on cran |
4 Müller, S., Rufibach, K. (2008). On the max-domain of attraction of distributions with log-concave densities. Statist. Probab. Lett., 78(12), 1440-1444. doi |
3 Balabdaoui, F., Rufibach, K. (2008). A second Marshall inequality in convex estimation. Statist. Probab. Lett., 78(2), 118-126. doi |
2 Rufibach, K. (2007). Computing Maximum Likelihood Estimators of a log-concave Density Function. J. Stat. Comput. Simul., 77(7), 561-574. doi | R package on cran |
1 Rufibach, K., Bertschy, M., Schüttel, M., Vock, M., Wasserfallen, T. (2001). Eintrittsraten und Austrittswahrscheinlichkeiten EVK 2000. Mitteilungen der Schweizerischen Aktuarvereinigung, 2001(1), 49-70. doi |

Invited discussions in statistical journals

1 Rufibach (2010). Proposal of the vote of thanks in discussion of Cule M. / Samworth R. and Stewart M.: Maximum likelihood estimation of a multidimensional logconcave density. J. R. Stat. Soc. Ser. B Stat. Methodol., 72(5), 577-578.

Letters to the editor in Statistical Journals

2 Hampson (2023). Biostatistical considerations when using RWD and RWE in clinical studies for regulatory purposes: A landscape assessment. Statistics in Biopharmaceutical Research, 15(1), 23-26.
1 Dukes (2021). On Identification of the Principal Stratum Effect in Patients Who Would Comply If Treated. Statistics in Biopharmaceutical Research, 13(4), 511-512.