生物統計

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.

Students are expected to be familiar with basic epidemiologic concepts.

無備註

Class website: http://ghuang.stat.nctu.edu.tw/course/biostat19/

作業部份: There are four homework assignments. 考試部份: One midterm exam and one final exam. 評量部份: The course grade will be based on four homework assignments (40%), one midterm exam (25%), and one final exam (35%).

• Introduction and overview of goals of epidemiologic research and epidemiologic study designs

• Measures of disease occurrence and association

  a. Different rates b. Inferences for rates c. Comparing two rates d. 2×2 table e. X2 test and Fisher's exact test f. R×C table g. Relative risk and odds ratio h. Inferences for relative risk and odds ratio

• 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

• 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

• Confounding and interaction in logistic regression

  a. Modeling b. Assumption c. Interpretation

• 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

• 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

• 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

• Analysis of survival data

  a. Examples of survival data b. Survival, hazard and cumulative hazard functions c. Censoring and truncation d. Kaplan-Meier estimator

• Proportional hazards model

  a. Assumption of the model b. Testing and estimation c. Computing programs and interpreting results d. Time dependent covariates

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. McCullagh P, Nelder JA (1989). Generalized Linear Models, 2nd edition, Chapman and Hall.

地點

423 Joint Education Hall

時間

By appointment

聯絡方式

Guan-Hua Huang, Ph.D. Office: 423 Joint Education Hall Phone: 03-513-1334 Email: ghuang@stat.nctu.edu.tw