Anova Multivariable Linear Regression Analysis

For the analysis

- All participants should have access to complete information on each analysis variable (BMI and Glucose. Angina, Stroke. CVD. Hypertension).
- To perform a multivariable linear analysis using BMI (or SPSS), and other independent variables such as Glucose and Angina, Stroke and CVD, hypertension as dependent variables, you will need a statistical package like R or SPSS.
- To determine the relationship between each variable and BMI, examine each coefficient.
- Comparing the effects of multivariables and crude will show if any differences exist. If they are, then consider which variables might be contributing.

The null hypothesis H0 is not rejected. This would indicate that BMI is related to patient characteristics such as Glucose and Stroke in Framingham Heart Study. The null hypothesis would not be rejected, which would indicate that these variables are unrelated.

Important to remember that specific analysis results will vary depending on what data and variables are used as well as which statistical software package was used and the methods employed.