Exam 2024
Procedures
- Submit your answers in Blackboard
- Provide Jupyter output and code in PDF format
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Provide all answers (include images of the network) in a single Word document
Assignment
Question 1: What is your name, email, and phone number.
Question 2: In the following data examine the impact of remission. Adjust the hyper-parameter until weight gain is
a predictor of remission. Because there are very few variables in these data, there is no need to
drop variables and the hyper-parameter is likely to be near 0. Do not drop
regressions because of low percent of variation explained. Do not drop
coefficients because of small effect sizes. The variables occur in
the following temporal order: Age, Gender, Psychosis, Antidepressant,
Weight Gain, and Remission.
- What are parents in the Markov Blanket of Antidepressant?
- Regress all variables on preceding variables. Display a
summary table of these regressions showing McFadden R-squared,
intercept, and regression coefficients.
- Construct a network model using
regressions. show each variable as a node. Draw arcs from preceding
variable to next associated variable. Estimate probability of each
node in the network. Display the Table for predicting remission
from joint distribution of significant predictors. Display the
probability of remission when we have no information about the
variables.
- Create a counterfactual regression. Report the McFadden R squared,
intercept, and coefficients for weight gain regressed on all preceding
variables but not on antidepressant.
- Construct a counterfactual model where the impact of
antidepressants is not mediated by weight gain. Display the
network and the predicted probability of remission.
- What is the causal impact of antidepressant on remission? This
analysis reports the causal impact as observed.
- What is the causal impact of antidepressant on remission using the
counterfactual model where the mediated impact of antidepressant
through weight gain has been removed?
- What percent of impact of the antidepressant on remission is mediated
through weight gain?
Following resources are available
This page is part of the course on Comparative Effectiveness by Farrokh Alemi, PhD Home►
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