STATISTICAL METHODS FOR EPIDEMIOLOGY
SPRING
2008
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Instructor: |
Guan-Hua Huang, Ph.D. |
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Office: 423 Joint Education Hall |
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Phone: 03-513-1334 |
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Email: ghuang@stat.nctu.edu.tw |
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Class meetings: |
Wednesday 9:00 - 12:00 at 407 Joint Education Hall |
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Office hours: |
By appointment |
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Class website: |
http://www.stat.nctu.edu.tw/subhtml/source/teachers/ghuang/course/statepi08/ |
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Credit: |
Three (3) credits |
COURSE SUMMARY
This course will cover statistical methods for
design, conduct, and analysis of epidemiologic studies such as case-control and
cohort studies. Topics include overview of designs for research studies;
epidemiologic study design; rates and risk; measures of association; classical
contingency table methods; logistic and Poisson regression; and proportional
hazard regression. Examples from the literature and data from a number of
well-known epidemiologic studies will be used for illustration of the concepts
involved.
HANDOUTS AND
TEXTBOOKS
Handouts corresponding to each lecture will be
available on the class website before each class. There is no required textbook for this course. Following books are recommended
for further reading:
Nicholas P. Jewell
(2003). Statistics
for Epidemiology. CRC Press.
Breslow NE, Day NE (1980). Statistical Methods in
Cancer Research, Vol. I, The Analysis of Case-Control Studies. International
Agency for Research on Cancer, Lyon.
Breslow NE, Day NE (1987). Statistical Methods in
Cancer Research, Vol. II, The Design and Analysis of Cohort Studies.
International Agency for Research on Cancer, Lyon.
Hosmer
DW, Lemeshow S (1989). Applied Logistic Regression,
John
Wiley & Sons.
PREREQUISITES
Students are expected to
be familiar with basic epidemiologic concepts. The prerequisite
for this course is “Introduction to
Epidemiology”, or equivalent.
METHOD OF STUDENT
EVALUATION
The course grade will be based on four homework assignments (40%), one midterm exam (25%), and one final exam (35%).
COURSE OUTLINE
Nicholas P. Jewell
(2003): Statistics for Epidemiology (Jewell),
Breslow NE, Day NE (1980): Statistical Methods in
Cancer Research, Vol. I (Breslow & Day I),
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Module |
Topic |
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1 |
Introduction and overview of goals of
epidemiologic research and epidemiologic study designs |
Jewell Chapter 1, 5 Breslow & Day I Chapter 1 Breslow & Day II Chapter 1 |
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2 |
Measures of disease occurrence
and association: a.
Different
rates b.
Inferences
for rates c.
Comparing
two rates d.
2×2 table e.
c2 test and Fisher’s exact test f.
R×C
table g.
Relative
risk and odds ratio h.
Inferences
for relative risk and odds ratio |
Jewell Chapters 2, 4, 6, 7 Breslow & Day I Chapter 2, 4 |
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3 |
Control of extraneous
factors: a.
Confounding
and interaction b.
Mantel-Haenszel
method c.
Analysis
of matched data- McNemar’s test d.
Measure
of agreement- Kappa statistic |
Jewell Chapter 8, 9, 10, 11 |
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4 |
Logistic regression: a.
Concepts b.
Model
and assumption c.
Interpretation
of regression coefficients d.
Inferences e.
Likelihood
ratio test f.
Goodness-of-fit
test g.
Residual
plot |
Jewell Chapter 12, 13 Hosmer
& Lemeshow Chapter 1, 2 |
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5 |
Confounding and
interaction in logistic regression: a.
Modeling b.
Assumption c.
Interpretation |
Jewel Chapter 14 |
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6 |
Logistic regression for
contingency tables: a.
Modeling
of 2×2 table b.
Modeling
of 2×2×2 table c.
Modeling
of K×2 table d.
Modeling
of M×2×2 table |
No reading |
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7 |
Logistic regression for case-control and
matched data: a. Risk and odds ratio in case-control studies b. Logistic regression for case-control data c. When there are many strata with few observations in each d. Conditional logistic regression for matched data |
Jewell Chapter 16 Hosmer
& Lemeshow Chapter 7 |
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8 |
Poisson regression for
count data: a.
Introduction
to generalized linear model b.
Poisson
regression c.
Application
to cohort study d.
Log
linear model for contingency table |
Breslow & Day II Chapter 4 |
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9 |
Analysis of survival
data: a.
Examples
of survival data b.
Survival,
hazard and cumulative hazard functions c.
Censoring
and truncation d.
Kaplan-Meier
estimator |
Breslow & Day II Chapter 5 |
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10 |
Proportional hazards
model: a.
Assumption
of the model b.
Testing
and estimation c.
Computing
programs and interpreting results d.
Time
dependent covariates |
Breslow & Day II Chapter 5, 6 |