
Email:
andrea.riebler@ntnu.no
Mail Address:
Department of Mathematical Sciences
Norwegian University of Science and Technology
N-7491 Trondheim
Norway
Office:
Sentralbygg 2, 12th floor, Gløshaugen
Tel: +47 735 93528
Andrea joined the Statistics group at the Department of Mathematical Sciences in March 2013. She completed her Ph.D in 2010 at the Department of Biostatistics of the University of Zurich (UZH) under the supervision of Leonhard Held. In 2011 she received a postdoctoral "Forschungskredit" fellowship from UZH to work on her own project on genome-scale count data. She worked also as a postdoctoral student for Mark Robinson at the Institue of Molecular Life Sciences at UZH in the area of statistical genomics.
Research interests
My research interests lie in biostatistical applications, spatial statistics, computational statistics and Bayesian inference.I am the principal investigator of the Norwegian Research Council funded project Penalized Complexity-priors: A new tool to define default priors and robustify Bayesian models (08/2015-07/2021). This project aims to create a framework for specifying intuitive and robust joint priors for several variance parameters in a latent Gaussian model. The end goal is an R package that allows the developed framework to be easily used by all scientists fitting latent Gaussian models.
I am invoved in the development of the R-package SUMMER (Spatio-Temporal Under-Five Mortality Methods for Estimation) which implements various methods for spatial and spatio-temporal smoothing of complex survey data. The focus is on subnational mapping of health and demographic indicators, e.g. under-five mortality, from low- and medium income countries.This work is lead by Jon Wakefield at the University of Washington, Seattle, USA.
I am in the developing/maintaing team of the Integrated nested Laplace approximations (INLA) software.
I am an international collaborator for the project “Anomaly in the gradient: Health of U.S. adults with subbaccalaureate education” of which Dr. Anna Zajacova from the Western University in London Ontario is the principal investigator. The project had been granted by the the National Institute of Health (NIH) for the project period 05/15/2016–04/30/2018 (award number R03AG050130), but is still on-going. I act as a statistical consultant in this project and will assist Dr. Zajacova to implement and apply multivariate Bayesian age-period-cohort models to analyze various health inicators collected via survey studies .
Recent publications/preprints:
- Fuglstad, Geir-Arne; Hem, Ingeborg Gullikstad; Knight, Alexander; Rue, Håvard; Riebler, Andrea Ingeborg. (2020) Intuitive Joint Priors for Variance Parameters. Bayesian Analysis. vol. 15 (4).
- Hem, Ingeborg Gullikstad; Selle, Maria; Gorjanc, Gregor; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg. (2020) Robust Modelling of Additive and Non-additive Variation with Intuitive Inclusion of Expert Knowledge. Genetics. In press
- Paige, John; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Wakefield, Jon. (2020). Design- and Model-Based Approaches to Small-Area Estimation in a Low and Middle Income Country Context: Comparisons and Recommendations. Journal of Survey Statistics and Methodology. In press.
- Wakefield, Jon; Fuglstad, Geir-Arne; Riebler, Andrea Ingeborg; Godwin, Jessica; Wilson, Katie; Clark, Samuel J. (2019). Estimating under-five mortality in space and time in a developing world context. Statistical Methods in Medical Research. vol. 28 (9).