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1.
Spiegel, E ; Kneib, T.* ; von Gablenz, P.* & Otto‐Sobotka, F.*: Generalized expectile regression with flexible response function. Biom. J. 63, 1028-1051 (2021)
2.
Kurz, C.F. & Stafford, S.*: Isolating cost drivers in interstitial lung disease treatment using nonparametric Bayesian methods. Biom. J. 62, 1896-1908 (2020)
3.
Deffner, V.* et al.: Mixtures of Berkson and classical covariate measurement error in the linear mixed model: Bias analysis and application to a study on ultrafine particles. Biom. J. 60, 480-497 (2018)
4.
Köhler, M. et al.: Flexible Bayesian additive joint models with an application to type 1 diabetes research. Biom. J. 59, 1144-1165 (2017)
5.
White, I.R.* ; Rapsomaniki, E.* & Emerging Risk Factors Collaboration (Meisinger, C.): Covariate-adjusted measures of discrimination for survival data. Biom. J. 57, 592-613 (2015)
6.
Heim, S.* ; Hahn, K.R. ; Auer, D.P.* & Fahrmeir, L.*: Diffusion tensor magnetic resonance imaging in human brain research. Biom. J. 46, 1, S.18 (2004)
7.
Wellmann, J.: Robustness of an S-Estimator in the One-Way Random Effects Model. Biom. J. 42, 215-221 (2000)
8.
Lasser, R. & Obermaier, J.: The Influence of the Incubation Period to Qualitative Aspects of the Spread of AIDS. Biom. J. 31, 833-839 (1989)
9.
Tritschler, J.: A Semi-Markov Modell for the Progression of the HVI-Infection. Biom. J. 2 (1989)
10.
Chambless, L.: On the Use of Two-Stage Cluster Samples in Epidemiological Population Studies. Biom. J. 30, 313-328 (1988)
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