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This course is an introduction to the fundamental concepts in biostatistics
and their use in clinical research. Through directed readings and discussion
of representative research reports from peer-reviewed journals, students
will be introduced to the concepts of hypothesis formulation, descriptive
statistics, commonly used research designs and statistical tests, statistical
significance, confidence intervals, statistical power, and commonly used
statistical models. In addition, the basic concepts of data collection
and analysis will be presented using Microsoft Access and SAS. 4 credits.
(Degree Requirement)
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NIH Warren G. Magnuson Clinical Center in collaboration with Duke University Medical Center © 2001 DUMC | Modified 01/16/02 |
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General principles
and issues in clinical research design. Formulating the research objective
and the research hypothesis; specifying the study population, the experimental
unit and the response variable(s). Classification of studies as experimental
or observational, prospective or retrospective, case-control, cross-sectional,
or cohort; their relative advantages and limitations and the statistical
methods used in their analysis. Emphasis is placed on the traditional
topics of clinical epidemiology such as disease etiology, causation,
natural history, diagnostic testing, and the evaluation of treatment
efficacy. In addition, an introduction to ethical issues in clinical
research is included. Corequisite: CRP-241. 4 credits. (Degree Requirement)
A practical foundation
in economic evaluation of medical diagnostic procedures and therapeutic
interventions. The focus is on the development, analysis, and communication
of economic data in the context of clinical research. Topics include:
basic finance and organization of health care, evidence tables, utility
theory, tree-structured decision models, health care cost accounting,
cost-effectiveness, cost-utility and cost-benefit analysis, special
statistical issues in analysis of economic data. Prerequisite: CRP-242.
2 credits.
This course extends
CRP 241 (Introduction to Statistical Methods) to more advanced topics
relevant in clinical research. Topics include regression models (linear
and logistic regression models, their practical applications in assessing
multivariable relationships and formulating predictive models, and the
interpretation of model parameters), categorical data analysis (methods
for analyzing nominal and ordinal response variables) and survival analysis
(inferences from time-to-event data with censored observations, including
Kaplan-Meier curves, hazard functions, and the Cox proportional hazards
regression model). Prerequisite: CRP-241. 4 credits. (Degree Requirement)
A survey of unique
challenges related to creating, managing, and completing clinical research
projects, with focus on the methods used to set up systems and solve
problems that maximize timeliness, accuracy, efficiency, and validity
of the results. The structural framework is based on identification
of the components necessary to perform a successful clinical research
project and development of an understanding of how these components
function and interact. A variety of types of clinical research projects
will be used as examples. Includes the responsible conduct of research.
Prerequisite: CRP-242. 4 credits. (Degree Requirement)
This seminar integrates
and builds on the core courses to provide practical experience developing
and critiquing the methodological aspects of clinical research protocols
and the clinical research literature. Assigned readings are drawn from
contemporary literature and include both exemplary and flawed studies.
Prerequisites: CRP-242 and CRP-245. 2 credits. (Degree Requirement)
Fundamental concepts
in the design and analysis of clinical trials are examined. Topics include
protocol management, sample size calculations, determination of study
duration, randomization procedures, multiple endpoints, study monitoring,
and early termination. Prerequisite: CRP-245. 2 credits.
Research methods in
health services research. Topics include measurement of health-related
quality of life, case mix and comorbidity, quality of health care and
analysis of variations in health care practice. Advantages and disadvantages
of studies that use large databases as well as advanced methods in analysis
and interpretation of health services outcomes will be addressed. This
includes application of traditional research designs (e.g., randomized
trials) to address health services research questions and the interface
between health services research and health policy. Prerequisites: CRP-242
and CRP-245. 2 credits.
An introduction
to methods associated with the analysis of human genetic data, with
a focus on applied projects aimed at identifying genes leading to human
disease. The course provides an overview of modern techniques in the
analysis of complex human disease, with a focus on statistical techniques.
Topics include: how a trait is determined to have a genetic component,
basic genetic concepts, study design and sampling strategies, testing
Hardy-Weinberg equilibrium, utilization of linkage maps, detection and
location of genes using linkage disequilibrium and other methods, gene-environment
interactions, and a molecular overview of DNA techniques and evolving
methodologies (SNPs, microarray analysis, etc). Students will be introduced
to specialized software and internet-based resources for the analysis
of genetic data. Prerequisites: CRP 241 and basic knowledge of genetics.
2 credits.
An introduction to
the elements of psychometric theory that are relevant to the conduct
of clinical research. Topics include issues in questionnaire and scale
design, types of scales, scale construction and validation; definition,
measures and estimation of reliability and validity; statistical issues
resulting from unreliability (such as the effect of reliability on sample
size estimation); and methods for assessing the psychometric properties
of scales (such as factor analysis and Cronbach's alpha). Prerequisites:
CRP-242 and CRP-245. 2 credits.
This
course provides an introduction to the scientific principles of rational
drug therapy and contemporary drug development. Topics in the first
module include the pharmacokinetics of drug absorption, distribution
and elimination in healthy individuals, in patients with impaired organ
function, and in populations of study subjects. The second module focuses
on the biochemical and pharmacogenetic aspects of drug metabolism, and
on the pharmacokinetic and pharmacodynamic basis of drug interactions.
2 credits.
An individualized
research project under the direction and supervision of the student's
mentor and examining committee. 12 credits.