Proposals for project/masterthesis topics for 2018/2019
I choose to provide no concrete thesis topics but rather outline the research fields I am interested in, see also here.
I am interested in Bayesian inference with application to biostatistics, in particular statistical methods for epidemiological data,
computerintensive methods and measurement error/spatial misalginment analysis. I am using mostly INLA for full Bayesian inference
At the moment, I am interest in:

Modeling data arising from complex survey designs:
In developing countries there exist commonly no disease or mortality registers. Mortality rates and other characteristics are thus commonly estimated using surveys.
In current work we estimated under 5 mortality rates in Africa, see here:
Wakefield, J., Fuglstad, GA, Riebler, A., Godwin, J., Wilson, K. and Clark, S.J. "Estimating Under Five Mortality in Space and Time in a Developing World Context" Another project tries to understand the health of American adults who attended but did not complete college—the subbaccalaureate group  compared to higher or lower education groups. Data are obtained from three large, nationallyrepresentative survey studies.
A potential project/master thesis could start by doing a literature review, relevant papers might be: Wakefield and Skinner (2017). "Introduction to the Design and Analysis of Complex Survey Data", Statistical Science. Volume 32, Number 2 (2017), 165175.
 Diggle, P. J., Menezes, R., & Su, T. L. (2010). Geostatistical inference under preferential sampling. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(2), 191232.
 McCormick, T.H., Li, Z.R., Calvert, C., Crampin, A.C., Kahn, K. and Clark, S.J., 2016. Probabilistic causeofdeath assignment using verbal autopsies. Journal of the American Statistical Association, 111(515), pp.10361049.

Making INLA more userfriendly: Currently great effort is spend in making the Bayesian software INLA more userfriendly. A review paper currently appeared
 Rue, H., Riebler, A., Sørbye, S.H., Illian, J.B., Simpson, D.P. and Lindgren, F.K., 2017. Bayesian computing with INLA: a review. Annual Review of Statistics and Its Application, 4, pp.395421.
 Wang, C., Puhan, M. A., Furrer, R., & SNC Study Group. (2018). Generalized spatial fusion model framework for joint analysis of point and areal data. Spatial Statistics, 23, 7290. Wang, C., Puhan, M. A., Furrer, R., & SNC Study Group. (2018). Generalized spatial fusion model framework for joint analysis of point and areal data. Spatial Statistics, 23, 7290.

How to do model comparison in a Bayesian setting:
Doing model comparison in a Bayesian setting is very controversial. Which measure should be used? A project might investigate different measures and compare them
in different applications.
 Gelman, A., Hwang, J., & Vehtari, A. (2014). Understanding predictive information criteria for Bayesian models. Statistics and Computing, 24(6), 9971016.
 Vehtari, A., Gelman, A. and Gabry, J., 2017. Practical Bayesian model evaluation using leaveoneout crossvalidation and WAIC. Statistics and Computing, 27(5), pp.14131432.
 Held, L., Bové, D.S. and Gravestock, I., 2015. Approximate Bayesian model selection with the deviance statistic. Statistical Science, 30(2), pp.242257.
Project/Mastertheses will typically combine methodological work, their implementation and application to simulated and/or real world data. A recommended course in this aspect is TMA4300 Computer intensive statistical methods