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, polytomous logistic, proportional odds 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/biostat21/ Google meet線上直播網址: https://meet.google.com/cso-mfvj-ukj

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

• Nonparametric methods

  a. Sign test b. Wilcoxon signed-rank test c. Wilcoxon rank-sum test (Mann-Whitney test) d. Kruskal-Wallis test e. Spearman rank correlation

• Multiple comparison procedures

  a. Family-wise error rate, false discovery rate b. Adjusted p-value c. Bonferroni procedure d. Sidak procedure e. Holm procedure f. Hochberg procedure g. Benjamini-Hochberg procedure

• 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 data and conditional logistic regression

  a. Case-control studies b. Risk and odds ratio in case-control studies c. Logistic regression for case-control data d. When there are many strata with few observations in each e. Conditional logistic regression for matched data

• Analysis of polytomous data

  a. Polytomous data: nominal versus ordinal scale b. Model for nominal scales (polytomous logistic regression) c. Model for ordinal scales (proportional odds model)

• Poisson regression and log-linear model

  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

• One-sample estimation for survival data

  a. Parametric models for complete and censored data b. Nonparametric models for complete and censored data c. 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

• Two-sample testing for survival data

  a. Complete failure times b. Censored failure times c. Log-rank test

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 (Jewell) Breslow NE, Day NE (1980): Statistical Methods in Cancer Research, Vol. I (Breslow & Day I) Breslow NE, Day NE (1987): Statistical Methods in Cancer Research, Vol. II (Breslow & Day II) Hosmer DW, Lemeshow S (1989): Applied Logistic Regression (Hosmer & Lemeshow) McCullagh P, Nelder JA (1989): Generalized Linear Models, 2nd edition (McCullagh & Nelder) Klein, Moeschberger (2003). Survival Analysis: Techniques for Censored and Truncated Data, 2nd edition. (Klein & Moeschberger)

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@nycu.edu.tw