Highlights
The Framingham Heart Study has been a leader in the development and dissemination of multivariable statistical models to estimate the risk of coronary heart disease. Each attribute is a potential risk factor. There are both demographic, behavioural and medical risk factors.
Multiple Regression:
1. [2] Consider systolic Blood Pressure as response variable and compute a regression model based on male, age, BMI, BPMeds, glucos and totChol. (Model 1)
2. [1] Is there any evidence to keep all variables in your regression model - Model 1?
3. [2] Compute the reduced model based on the results of previous part. (Model 2)
4. [1] Consider Model 1 as Full and Model 2 as Reduced, apply F-test to compare these two models, write all 5 steps of testing.
5. [3] Consider “totChol” as response variable and compute regression model based on male, age, education (as Dummy variable), diabetes, sysBP, BMI and glucose (Model 3)
6. [1] Is there any evidence to keep all variables in your regression model 3? α = 0.1
7. [1] Compute the reduced model based on the results of previous part. (Model 4) item [2] Apply stepwise regression for Model 3 based on AIC to select the best model.
8. [2] Test for model assumptions by using diagnostic analysis for Model 4
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