silvialiverani/PReMiuM-R-package

PReMiuM R package

R package PReMiuM

The main references for the PReMiuM package are:

• Liverani, S., Hastie, D. I., Azizi, L., Papathomas, M. and Richardson, S. (2015) PReMiuM: An R package for Profile Regression Mixture Models using Dirichlet Processes. Journal of Statistical Software, 64(7), 1-30.

• A practical manual available at https://premium-r-package.readthedocs.io/en/latest/, with additional information also at http://envirotyping.readthedocs.io/en/latest/manual/

See the package's page on CRAN with the latest released version: https://cran.r-project.org/web/packages/PReMiuM/index.html

Some papers about or using PReMiuM:

• Coker E., Liverani S., Su J. G. and J. Molitor (2018) Multi-Pollutant Modeling Through Examination of Susceptible Subpopulations Using Profile Regression. Current Environmental Health Reports (to appear).

• Liverani S., Lavigne A. and Blangiardo M. (2016) Modelling collinear and spatially correlated data. Spatial and Spatio-temporal Epidemiology 18, 63-73.

• Mattei F., Liverani S., Guida F., Matrat M., Cenée S., Sanchez M., Luce D., Richardson S., Stücker I., and the Icare Study Group. (2016) A multidimensional analysis of the effect of occupational exposure to organic solvents on lung cancer risk: the ICARE study. Occupational and Environmental Medicine 73 (6), 368-377.

• Coker E., Liverani S., Ghosh J., Jerrett M., Beckerman B., Su J., Li A., Ritz B., Molitor J. (2016) Multipollutant Exposure Profiles Associated with Term Low Birth Weight in Los Angeles County. Environment International, 91, 1-13.

• Coker E., Jerrett M., Ghosh J., Gomez-Rubio V., Beckerman B., Cockburn M., Liverani S., Su J., Li A., Ritz B., Molitor J. (2015). Geography of Risk: Modeling Spatial Effects of Air Pollutants on Preterm Birth and Low Birth Weight in Los Angeles County. Environmental Research 142, 354-364.

• Pirani, M., Best, N., Blangiardo, M., Liverani, S., Atkinson, R. W., and G. W. Fuller (2015) Analysing the health effects of simultaneous exposure to physical and chemical properties of airborne particles. Environment International, 79, 56-64.

• Hastie, D. I., Liverani, S. and Richardson, S. (2015) Sampling from Dirichlet process mixture models with unknown concentration parameter: Mixing issues in large data implementations. Statistics and Computing 25 (5), 1023-1037.

• Molitor, J., Brown, I. J., Papathomas, M., Molitor, N., Liverani, S., Chan, Q., Richardson, S., Van Horn, L., Daviglus, M. L., Stamler, J. and Elliott, P. (2014) Blood pressure differences associated with DASH-like lower sodium compared with typical American higher sodium nutrient profile: INTERMAP USA. Hypertension 64 (6), 1198-1204.

• Hastie, D. I., Liverani, S., Azizi, L., Richardson, S. and Stucker I. (2013) A semi-parametric approach to estimate risk functions associated with multi-dimensional exposure profiles: application to smoking and lung cancer. BMC Medical Research Methodology. 13 (1), 129.