Series lectures
Speaker: Dr. Jinhui Zhao
Date: October 27 to November 13, 2015
| Lecture | Content of lecture | Date | time | Room |
| Part I | Statistical analyses using SAS | | | |
| Lecture 1 | Statistical analyses using SAS/STAT procedures | Oct 27 & 28 | 18:00-20:00 | 1412 |
| Lecture 2 | Design effects in complex survey data 2.1. What are design effects 2.2. How to control for design effects in survey analysis 2.3. SAS survey procedures | Oct 29 & 30 | 18:00-20:00 | 1412 |
| Lecture 3 | Choose correct analysis for various survey designs 3.1. Simple random sampling 3.2. Stratified sample 3.3. One-stage cluster sampling 3.4. Probability proportional to size sampling 3.5. Stratified random sampling 3.6. Systematic sampling 3.7. Repeated systematic sampling 3.8. Stratified random sampling with allocation to strata 3.9. Regression estimation | Oct 31 & Nov 1 | 18:00-20:00 | 1412 |
| Part II | Meta-analysis and meta-regression | | | |
| Lecture 4 | Complex data structures 4.1. Independent groups within a study 4.2. Multiple outcomes within a study 4.3. Multiple comparisons within a study 4.4. Perform meta-analysis using SAS | Nov 2 & 3 | 18:00-20:00 | 1412 |
| Lecture 5 | Meta-regression 5.1. Introduction 5.2. Fixed-effects model 5.3. Random-effects model 5.4. Perform meta-analysis using SAS Proc Mixed | Nov 4 & 5 | 18:00-20:00 | 1412 |
| Lecture 6 | Cumulative meta-analysis 6.1. What is a cumulative meta-analysis 6.2. Why to perform a cumulative meta-analysis 6.3. How to perform a cumulative meta-analysis | Nov 6 & 7 | 18:00-20:00 | 1412 |
| Lecture 7 | Heterogeneity 7.1. Overview 7.2. Identifying and quantifying heterogeneity 7.3. Subgroup analyses 7.4. Meta-analysis 7.5. Perform meta-analysis using SAS | Nov 8 & 9 | 18:00-20:00 | 8日（1412) 9日（2400） |
| Lecture 8 | Publication bias 8.1. The problems of missing studies 8.2. How to detect publication bias 8.3. Methods for addressing bias | Nov 10 | 18:00-20:00 | 1412 |
| Part III | Interrupted time series data | | | |
| Lecture 9 | 9.1. Time series data 9.2. Methods for analyzing time series data 9.3. Interrupted time series model 9.4. Analyze time series using SAS ARIMA procedure | Nov 11 - 13 | 18:00-20:00 | 1412 |