What model of multiple regression do I use to see if two independent variables affect a dependent variable, I also need to use two dummy variables?

Question

I need to explore the determinants of wheat yield using multiple regression. There are 120 observations. Do I need to use ANOVA? I am using R studio. My results need to include a consideration of more than one functional form, one or more interaction terms for a select set of variables, and the use of dummy variables.

Variable Descriptions:

yld wheat yield in kg/ha  
R Growing season rainfall (mm)  
N nitrogen fertilization rate (kg/ha)  
PrevCereal 1 if precious crop was a cereal, 0 otherwise  
RegionCode Location code (0/1)  

Answer 1

Just a simple guide as it's an assignment - don't want to ruin all the fun.

I often use the rms package.

1. Enter your model with splines for the continuous variables (use the rcs() spline as it works best with the rms package) and any possible interactions.
2. Check the general model assumptions - if you have issues try bootstrapping with the bootcov() function
3. Check overall ANOVA with the anova() function in the rms package, it has very nice built-in tests for non-linearity that are very useful.
4. Rebuild your model depending on the ANOVA results

Hope this helps!