Biostatistics and Epidemiology (Bios 605)
Course Syllabus
Mission Statement
The course enables the student to develop and use indicators of
health and disease and their potential causes and to look for
relationships among these variables.
Course Goals
Develop ways to measure occurrence of exposure and disease
Design studies to look for associations between exposure and
disease
Conduct a formal survey to collect these measures
Use statistical analyses to assess the strength of these
associations
Textbooks
Kuzma, J. (1998) Basic Statistics for the Health Sciences, third
ed.
Mayfield Publishing Company, Mountain View, California.
Page, R., Cole, G. and Timmreck, T. (1995) Basic Epidemiological
Methods and Biostatistics. Jones and Bartlett Publishers,
Sudbury, Massachusetts.
Evaluation Methods
There will be two tests. The first will be shortly after the on
site
part of the course and the second before coming to
Tulane for the second session. Each exam will contribute one half
of the
grade. There will be problems and quizzes, but these will not be
graded.
Click on the topic number to locate the resources and problems
for that
topic.
Topic 1
Nature of Data
Introduction to course and use of web site
Determine if a variable is being measured as categorical without
order, categorical with order or continuous
Compute and interpret the appropriate measure of central
tendency for each type of data
Compute and interpret measures of variability for continuous data
Topic 2
Laws of Probability
Compute probabilities using the additive law
Compute probabilities using the multiplicative law for
independent events
Define conditional probability
Determine if two events are independent
Define and use sensitivity, specificity, predictive value + and
predictive value -
Topic 3
Crude, Specific and Adjusted Rates
Define and identify examples of proportion, risk and rate
Define a crude rate
Define a specific rate
Compute an adjusted rate using the direct method
Compute an adjusted rate using the indirect method
Describe the use of an adjusted rate
Topic 4
Incidence and Prevalence
Define incidence density
Compute incidence density given follow up data from a cohort
that was initially disease free
Compute cumulative incidence given follow up data from a cohort
that was initially disease free
Define point prevalence
Topic 5
Introduction to Hypothesis
Testing
Distinguish between practical significance and statistical
significance
Describe the role of the null hypothesis in statistical analyses
Define type I error, type II error and power
Describe the impact of degree of variability and desired
detectable difference on sample size requirements
Topic 6
Epidemiology Study Designs
Describe the common epidemiologic study designs including
observational study, cohort study and case-control study
Indicate situations in which it is appropriate to use each type
of design
Topic 7
Measures of Association between Exposure and Disease
Compute and interpret a relative risk
Compute and interpret an odds ratio
Put confidence bounds around an odds ratio and interpret the
results
Compute and interpret attributable risk
Indicate which measures of association can be computed from
data collected from each study design
Topic 8
Statistical Inference for Two Categorical Variables
Indicate when a chi square test of independence or a two sample
test of proportions is appropriate
Compute and interpret a chi square test of independence
Compute and interpret a two sample test of proportions
Compute and interpret a McNemar chi square test
Topic 9
Confounding
Define a confounder
Identify situations in which a confounder may exist
Determine if a variable is a confounder using the stratified
approach
Topic 10
Comparison of Groups when the Outcome is Continuous
Compute and interpret a two sample t test
Compute and interpret a paired t test
Indicate the appropriate use of a two sample t test and a paired
t test
Indicate the advantages and disadvantages of each
Topic 11
Methods of Data Collection
List some major data collection strategies and their
optimum uses
List and describe the types of data which can be obtained from a
formal survey
Identify properties of "good" and "poor" survey items and write
examples of each.
Topic 12
Reliability and Validity and Scale Development
Define and compute a correlation coefficient
Define reliability and identify factors that affect it
Describe test-retest, parallel forms and internal consistency
estimates of reliability and list the strengths and
weaknesses of each
Define validity and identify factors that affect it
Describe content, construct and criterion referenced validity and
describe ways n which each can be measured
Define a measurement scale
Indicate why measurement scales are useful
List the important properties of a measurement scale
Determine if the items in a scale are working together
(using binary items)
Topic 13
Bias in Epidemiologic Studies
Define the major types of bias in epidemiologic studies
Describe examples where each may occur
Identify strategies to minimize bias in epidemiologic studies
Topic 14
Evaluation Study Designs
Describe the common evaluation study designs including the single
group pretest-posttest design, two group pretest-
posttest design and the two group posttest only design
Define internal and external validity
Evaluate the examples of the study designs listed above with
respect to internal and external validity
Topic 15
Sampling
Define a simple random sample, a stratified random sample and a
cluster sample
Describe ways to conduct each type of sample
List the strengths and weaknesses of each kind of sample
Topic 16
Linear Regression
Interpret a simple linear regression
Indicate when it is appropriate to use these methods
Compute and interpret global F tests
Compute and interpret partial F tests
Topic 17
Effect Modification
Define interaction (effect modification)
Identify situations in which interaction may exist
Determine if interaction exists using the stratified approach
© J.Rice