Directed Acyclic Graphs (DAGs) (10 points)
To complete this section, please review the articles on DAGs in the Week 5 Learning Resources. You may use any drawing tools available to you to create the DAGs requested below, although it does not need to be sophisticated software; for example, Microsoft Word’s Insert Shapes and Text Box features are sufficient tools to create these diagrams.
For each of the following epidemiological scenarios, draw a DAG that represents the relationships between the variables: (5 points each)
Assessing Confounding in Multivariate Regression (20 points)
A researcher studied women with breast cancer to better understand the association between self-rated health and breast cancer mortality (Prehn, 1996). By using survival analysis, the following results were obtained from three different models:
Assessing and Interpreting Effect Modification (15 points)
Effect Measure |
Effect of Factor X (X+ Z-) |
Effect of Factor Z (X- Z+) |
Observed Joint Effect (X+Z+) |
A Positive or negative? |
B Additive or multiplicative? |
Attributable Risk |
20.0 / 1000 |
15.0 / 1000 |
60.0 / 1000 |
Positive |
|
Relative Risk |
3.0 |
2.0 |
4.0 |
||
Relative Risk |
2.0 |
3.0 |
6.0 |
Medicine 1 Group (n=100) |
Medicine 2 Group (n=100) |
|||
Cigarette smoker |
||||
Yes |
30 |
10 |
||
No |
70 |
90 |
||
Physically active |
||||
Yes |
35 |
35 |
||
No |
65 |
65 |
||
Discuss how you would determine if there is confounding and/or effect modification by cigarette smoking or physical activity in your study. Include details of any strategies you would use and provide specific examples using these study data. (5 points)
Reference:
Prehn, A. W. (1996). Self-rated health in middle-aged and elderly women with breast cancer (Doctoral dissertation). Retrieved from Dissertation Abstracts International.
WhatsApp us