STATS 209: Statistical Methods for Group Comparisons and Causal Inference (EDUC 260A, HRP 239)
Description
Critical examination of statistical methods in social science and life sciences applications, especially for cause and effect determinations. 
Topics: mediating and moderating variables, potential outcomes framework, encouragement designs, multilevel models, 
matching and propensity score methods, analysis of covariance, instrumental variables, compliance, path analysis and graphical models, 
group comparisons with longitudinal data. 
See http://rogosateaching.com/stat209/. Prerequisite: intermediate-level statistical methods.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit

2015-2016 Winter
STATS 209 | 3 units | Class # 35191 | Section 01 | Grading: Letter or Credit/No Credit | LEC 
01/04/2016 - 03/11/2016 Wed, Fri 1:30 PM - 3:20 PM at Sequoia Hall 200 

Week 1. Course Introduction;  properties of regression models
Week 2. Experiments vs observational studies;  Neyman-Rubin-Holland formulation
Week 3. Path analysis and causal modeling, multiple regression with pictures. Graphical models.
Week 4. Multilevel data. Contextual effects, aggregation bias, random effects models
Week 5. The many uses and forms of analysis of covariance (including regression discontinuity designs)
Week 6. Instrumental variable methods, simultaneous equations, reciprocal effects
Week 7. Compliance and experimental protocols; encouragement designs; intent to treat
Week 8. Matching and propensity score methods
Week 9. Time-1, Time-2 group comparisons for experimental and non-experimental designs:
Dead Week. Overflow and course summary. 

Case Studies in Cause and Effect