This area provides training in the development and application of new methods in epidemiologic research. Students learn to use and justify classical epidemiologic methods in study design, data analysis, and interpretation of results. Students also receive training in biostatistical areas most relevant to epidemiologic research. Recent innovations in epidemiologic methodology are introduced through advanced courses and tutorials. Doctoral students conduct research with faculty members in the development of new methodologies and in novel applications of existing methodologies. Those enrolling in this area of interest ordinarily have completed four semesters of college calculus and one semester of linear algebra. Students engaged in this area will have an opportunity for collaboration with researchers working on causal inference in epidemiology and allied sciences. Another option for collaboration is with a cross-departmental group of epidemiologists and biostatisticians working on methods to adjust for bias due to exposure measurement error in nutritional, environmental and occupational health research. Students with degrees in computer science, mathematics or statistics are especially encouraged to apply to this area.