Maringe, C; Pashayan, N; Rubio, FJ; Ploubidis, G; Duffy, SW; Rachet, B; Raine, R; (2018) Trends in lung cancer emergency presentation in England, 2006-2013: is there a pattern by general practice? BMC cancer, 18 (1). p. 615. ISSN 1471-2407 DOI: https://doi.org/10.1186/s12885-018-4476-5

Maringe, C; Rachet, B; Lyratzopoulos, G; Rubio, FJ; (2018) Persistent inequalities in unplanned hospitalisation among colon cancer patients across critical phases of their care pathway, England, 2011-13. British journal of cancer. ISSN 0007-0920 DOI: https://doi.org/10.1038/s41416-018-0170-2

Rubio, F; Steel, M; (2018) Flexible linear mixed models with improper priors for longitudinal and survival data. Electronic journal of statistics, 12 (1). pp. 572-598. ISSN 1935-7524 https://projecteuclid.org/euclid.ejs/1519700495 Full text not available from this repository.

Rubio, FJ; Remontet, L; Jewell, NP; Belot, A; (2018) On a general structure for hazard-based regression models: An application to population-based cancer research. Statistical methods in medical research. p. 962280218782293. ISSN 0962-2802 DOI: https://doi.org/10.1177/0962280218782293 Item availability may be restricted.

Villa, C; Rubio, FJ; (2018) Objective priors for the number of degrees of freedom of a multivariate t distribution and the t-copula. Computational statistics & data analysis, 124. pp. 197-219. ISSN 0167-9473 DOI: https://doi.org/10.1016/j.csda.2018.03.010 Item availability may be restricted.

Dette, H; Ley, C; Rubio, F; (2017) Natural (Non-)Informative Priors for Skew-symmetric Distributions. Scandinavian Journal of Statistics. n/a-n/a. ISSN 1467-9469 DOI: https://doi.org/10.1111/sjos.12306

Rossell, D; Rubio, FJ; (2017) Tractable Bayesian variable selection: beyond normality. Journal of the American Statistical Association. 0-0. ISSN 0162-1459 DOI: https://doi.org/10.1080/01621459.2017.1371025 Item availability may be restricted.

Rubio, FJ; Yu, KM; (2016) Flexible objective Bayesian linear regression with applications in survival analysis. Journal of applied statistics, 44 (5). pp. 798-810. ISSN 0266-4763 DOI: https://doi.org/10.1080/02664763.2016.1182138