## Lecture: Review of Independence
## Assigned Reading- Introduction to chi-square test Read►
- Statistical test of independence in 2 variables Slides►
- Statistical test of independence in 3 variables Slides►
- Independence test through Poisson regression Slides►
- Jee Vang's lecture on indpendence test through Mutual Information Slides►
## AssignmentFor this assignment you can use any statistical package including SQL or Excel. Work can be done in group's of two students but you cannot work with a student that you have previously teamed up with. A. For the following data:
- Estimate chi-square for complete independence, 3 joint independence models, and 3 homogenous models
- Which model best fits the data and why? Shruti's response► Aryan & Saeed's SQL►
B. In the following data, test which pair of variables
are independent and which pairs are associated. First calculate
the goodness of fit of a homogenous model (all main effects and all
pair wise associations). Then progressively remove one of the pairs from the
model until you can find a set of associations that fit the data. R code► Slides►
C. Select 3 variables from the STAR*D data and analyze the independence relationship among the variables. - Read about the STAR*D study protocol. Protocol►
- Download data. Use instructor's last name as password. Must enter password twice. Data 2010► Data 2003►
- Select 3 variables
- Test 1 complete independence, 3 joint independence, and 3 homogenous associations.
- Identify the most parsimonious model whose fit to the data cannot be rejected
- Describe the meaning of your insight.
## MoreFor additional information (not part of the required reading), please see the following links: - Independence and Bayesian networks Video►
- Introduction to probability models Read► Slide►
- Event time stratification Read►
- Bayes rule & independence Video►
- Estimating effects of nursing in clinical teams Read►
- Breaking nominal variables into binary variables Read►
- The relationship between chi-square statistics from matched and unmatched analyses Read►
- Jeff Lin's analysis of independence of 3 variables Read►
- Decomposable (independent) sub-graphs in 5 variable models Read►
- Visualizing conditional probability See►
This page is part of the course on Comparative Effectiveness Home► Email Instructor► |
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