Courses Taught by Veronica Berrocal

EPID778: Spatial Statistics for Epidemiological Data

  • Graduate level
  • Summer term(s)
  • 1 Credit Hour(s)
  • Instructor(s): Berrocal, Veronica
  • Last offered Summer 2016
  • Prerequisites: None
  • Advisory Prerequisites: Previous expericne with R is preferred, not required
  • Description: With the increasing availability of geographic information systems, spatial data have become more frequent in many disciplines, including public health and epidemiology. This course aims to provide an introduction to spatial statistical methods for epidemiological data, covering modeling approaches for the two different types of spatial data: point-referenced data, where the geographical coordinates of the observations have been recorded; and areal-averaged data, where summary statistics (e.g., number of disease cases by county, zip code, etc.) are reported for each areal unit. Topics covered include: exploratory analysis for spatial data, covariance functions, kriging, spatial regression; disease mapping, spatial smoothing; point processes, assessment of clustering, and cluster detection. Each lecture will feature a lab component, during which spatial analyses of datasets, made available to the participants, will be performed using the publically available R statistical software
  • Course Goals: With the increasing availability of geographic information systems, spatial data have become more frequent in many disciplines, including public health and epidemiology. This course aims to provide an introduction to spatial statistical methods for epidemiological data

EPID815: Modern Statistical Methods in Epidemiologic Studies

  • Graduate level
  • Fall term(s)
  • 4 Credit Hour(s)
  • Instructor(s): Park, Sung Kyun Berrocal, Veronica
  • Last offered Fall 2015
  • Prerequisites: EPID 600, BIOSTAT 523 and BIOSTAT 560 for epid students. Biostat 650, 651 for biostat students
  • Advisory Prerequisites: EPID 798 for epid students; BIOSTAT 695 for Biostat students
  • Description: The goal of this pilot course is to create an interdisciplinary educational experience for Ph.D. students in Epidemiology (also available as an optional elective for Masters students in Biostatistics) through a uniquely designed course that contains lectures on advanced biostatistical methods, but places them in the context of epidemiological applications.
  • Course Goals: Students enrolled in the class will learn about cutting edge statistical methods in these four contemporary topics that arise frequently in the present scientific context. These four topics are: (a) Modern techniques for model building and variable selection; (b) Methods for analyzing longitudinal data; (c) Spatial regression methods; (d) Methods for studies of interaction/effect modification. The course will equip the new generation epidemiologists with state-of-the-art statistical methods in these domains, and teach them the craft of translating a practical problem into mathematical equations. However, the entire theoretical learning process will be placed in the context of sophisticated modeling of data from large complex studies with a focused problem to solve. Data for the projects will come from two studies that Professors Park and Mendes de Leon are involved with: the Normative Aging Study (NAS) and the Chicago Health and Aging Project (CHAP).
  • This course is cross-listed with BIOSTAT698.
  • Syllabus for EPID815