Ph.D. Elective Course Descriptions
EPIDEMIOLOGIC ELECTIVE COURSES:
EPID 610 Staff
Environmental and Occupational Epidemiology
Semester course; 3 lecture hours. 3 credits. Prerequisites:
BIOS 543 and EPID 571. This course is
designed to provide students with an overview of the principles,
methods and content of
environmental and occupational epidemiology with a focus on
designing, conducting, and
interpreting studies on the effects of chemical and physical
agents. Students will critique published
occupational and environmental epidemiology studies, learn how
to evaluate the potential for
cause-effect relationships, and become familiar with the role
of epidemiology in human health risk
assessment. Each session will include a seminar component where
exercises are completed and/or
published papers will be critiqued and discussed.
EPID 620 Resa M. Jones, PhD, MPH
Cancer Epidemiology
Semester course; 3 lecture hours.
3 credits. Prerequisite: EPID 571. Covers general principles of carcinogenesis
and the genetics of cancer; domestic and international patterns in
cancer incidence and mortality; cancer surveillance and screening,
and their relation to cancer prevention; epidemiologic characteristics
and risk factors for cancers to the lung, breast, prostate, gastrointestinal
tract, pancreas, bladder, endometrium, ovary, cervix and skin, as
well as cancer in children and young adults; and the public health
implications of cancer. Additional focus on critical evaluation of
different methodological approaches used in cancer research and potential
biases inherent given study designs.
Spring semester
EPID 621 John Marr, MD, MPH, FACP
Infectious Disease Epidemiology
Semester course; 3 lecture hours. 3 credits. Prerequisite: EPID
571. This course will discuss the
origins of epidemiology and how epidemiology methods are continually
applied to the study of
communicable diseases. Several infectious diseases will be studied
in depth to show the
progression toward characterization of the natural history of
the diseases and how policies
regarding prevention have been defined. Smallpox, HIV/AIDS,
the hepatitis family of agents and a
vector-borne disease will be studied. In addition, the topic
of antibiotic resistance will be covered in
depth. How the epidemiology of an infectious agent relates to
bioterrorism also will be discussed.
EPID 622 Derek Chapman, MS, PhD
Sp. Topics: Maternal and Child Health
Semester course, 3 lecture hours, 3 credits. Prerequisite EPID
571. This course will expose
students to current issues in maternal and child health (MCH).
Students will learn about key MCH
topics including family planning, low birth weight, infant mortality,
birth defects, injury prevention,
and international MCH issues. Students will be able to describe
how epidemiology methods are
used to determine risk and protective factors for women and
children and describe how these data
guide public health policy and program planning efforts.
HGEN 603
Mathematical and Statistical Genetics
Semester course; 3 lecture hours. 3 credits. Prerequisite: BIOS
543-544 or equivalent. Provides an
introduction to the rudiments of theoretical and applied mathematical
population genetics including
the segregation of genes in families, genetic linkage and quantitative
inheritance. Emphasizes the
methods used in the analysis of genetic data.
HGEN 619
Quantitative Genetics
Semester course; 3 lecture hours. 3 credits. The effects of
genes and environment on complex
human traits with emphasis on: Genetic architecture and evolution;
nongenetic inheritance; mate
selection; developmental change; sex-effects; genotype-environment
interaction; resolving cause
from effect; design of genetic studies, statistical methods
and computer algorithms for genetic data
analysis.
BIOSTATISTICS ELECTIVES:
BIOS 513-514/STAT 513-514
Mathematical Statistics I-II
Continuous courses; 3 lecture hours. 3-3 credits. Prerequisite:
MATH 307. Probability, random
variables and their properties, distributions, moment generating
functions, limit theorems,
estimators and their properties; Neyman-Pearson and likelihood
ratio criteria for testing
hypotheses.
BIOS 524
Biostatistical Computing
Semester course; 3 lecture hours. 3 credits. The Statistical
Analysis System (SAS) is both a
powerful computer language and a large collection of statistical
procedures. Students learn how to
create and manage computer data files. Techniques for thorough
examination and validation of
research data are presented as the initial step of a complete,
computerized analysis. Descriptive
statistics are computed and statistical procedures such as t-tests,
contingency tables, correlation,
regression, and analysis of variance then applied to the data.
Special attention is paid to the
applicability of each procedure. Students are encouraged to
analyze their own or typical data from
their discipline.
BIOS 571
Clinical Trials
Semester course; 3 lecture hours. 3 credits. Concepts of data
management and statistical design
and analysis in single-center and multicenter clinical trials.
Data management topics include the
collection, edition, and validation of data. Statistical design
topics include randomization,
stratification, blinding, placebo- and active-control groups,
parallel and crossover designs, and
power and sample size calculations. Statistical analysis topics
include sequential and group
sequential methods.
BIOS 572
Statistical Analysis of Biomedical Data
Semester course; 3 lecture hours. 3 credits. Statistical methodology
for data sets frequently
encountered in biomedical experiments. Topics include analysis
of rates and proportions,
epidemiological indices, frequency data, contingency tables,
logistic regression, life-tables and
survival analysis.
BIOS 581
Applied Multivariate Analysis
Semester course; 3 lecture hours. 3 credits. Prerequisite: BIOS
544 or 554. Focuses on
multivariate statistical methods, including Hotelling’s
T-square, MANOVA, multivariate multiple
regression, canonical correlation, discriminant analysis, partially
and blocking, multivariate outliers,
components and factor analysis, and GMANOVA. Presumes the material
in BIOS 543-544 or BIOS
553-554, including a matrix approach to multiple regression.
