Publications
See also my profile on Google Scholar.
Books
ANOVA and Mixed Models: A Short Introduction Using R
Chapman & Hall/CRC The R Series, 2022.
Please visit the book's website for more information.
Logistische Regression: Eine anwendungsorientierte Einführung mit R (with M. Kalisch)
Springer Open Access, 2021.
Please visit the book's website for more information.
Wahrscheinlichkeitsrechnung und Statistik: Eine Einführung für Verständnis, Intuition und Überblick
Springer, 2020.
Please visit the book's website for more information.
Research Papers
- Anderegg, N., Hector, J. , Jefferys, L.F., Burgos-Soto, J., Hobbins, M.A., Ehmer, J., Meier, L., Maathuis, M.H. and Egger, M. (2020). Loss to follow-up correction increased mortality estimates in HIV-positive people on antiretroviral therapy in Mozambique. Journal of Clinical Epidemiology, 128, 83-92. Online Access.
- Klasen, J., Barbez, E., Meier, L., Meinshausen, N., Bühlmann, P., Koornneef, M., Busch, W. and Schneeberger, K. (2016) . A multi-marker association method for genome-wide association studies without the need for population structure correction. Nat Commun 7, 13299. Online Access.
- de Matos, N. M. P., Meier, L., Wyss, M., Meier, D., Gutzeit, A., Ettlin, D. A. and Brügger, M. (2016). Reproducibility of Neurochemical Profile Quantification in Pregenual Cingulate, Anterior Midcingulate, and Bilateral Posterior Insular Subdivisions Measured at 3 Tesla, Frontiers in Human Neuroscience, 10, Online Access.
- Meier, L. (2016). High-Dimensional Regression and Inference. In P. Bühlmann, P. Drineas, M. Kane and M.J. van der Laan (Eds.), Handbook of Big Data, 305-319. Chapman and Hall/CRC, Boca Raton, FL.
- Dezeure, R., Bühlmann, P., Meier, L. and Meinshausen, N. (2015). High-dimensional inference: confidence intervals, p-values and R-software hdi. Statistical Science, 30, 533-558. Online Access.
- Bühlmann, P., Meier, L. and van de Geer, S. (2014). Discussion on "A significance test for the Lasso (R. Lockhart, J. Taylor, R. Tibshirani and R. Tibshirani)". Annals of Statistics 42, 469-477. Online Access.
- Bühlmann, P., Kalisch, M. and Meier, L. (2014). High-Dimensional Statistics with a View Toward Applications in Biology. Annual Review of Statistics and its Applications 1, 255-278. Online Access.
- Schelldorfer, J., Meier, L. and Bühlmann, P. (2013). GLMMLasso: An algorithm for high-dimensional generalized linear mixed models using L1-penalization. Journal of Computational and Graphical Statistics. Online Access.
- Nicolai Meinshausen, Lukas Meier and Peter Bühlmann (2008). P-values for High-Dimensional Regression. Journal of the American Statistical Association 104, 1671-1681. Online Access.
- Meier, L., van de Geer, S. and Bühlmann, P. (2009). High-Dimensional Additive Modeling. Annals of Statistics 37, 3779-3821. Online Access.
- Hesterberg, T., Choi, N.H., Meier, L. and Fraley C. (2008) Least Angle and $\ell_1$ Penalized Regression: A Review. Statistic Surveys 2, 61-93 (electronic). Online Access.
- Schöner, D., Kalisch, M., Leisner, C., Meier, L., Sohrmann, M., Faty, M., Barral, Y., Peter, M., Gruissem, W. and Bühlmann, P. 2008. Annotating novel genes by integrating synthetic lethals and genomic information, BMC Systems Biology, 2:3. Online Access.
- Bühlmann, P. and Meier, L. (2008). Discussion on "One-step sparse estimates in nonconcave penalized likelihood models (H. Zou and R. Li)". Annals of Statistics, Volume 36, Number 4, 1534-1541. Online Access.
- Meier, L. and Bühlmann, P. (2007). Smoothing $\ell_1$-penalized estimators for high-dimensional time-course data, Electronic Journal of Statistics 1, 597-615 (electronic). Online Access.
- Meier, L., van de Geer, S. and Bühlmann P. 2008. The group lasso for logistic regression, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 70 (1), 53-71. Online Access.