I have multiple variables, E1,E2,E3,E4,E5,E6 are non binary variables and G1-G26 are indicator variables (0 or 1) . How would I be able to find up to 3rd order interactions for a linear regression equation, without receiving NA results for the summary output. When I run the following I receive NA for p-vales and std error:
M_raw2 <- lm( Y ~ (E1+E2+E3+E4+E5+G1+G2+G3+G4+G5+G6+G7+G8+G9+G10+G11+G12+G13+G14+G15+G16+G17+G18+G19+G20+G21+G22+G23+G24+G25)^3, data=newef )
summary(M_raw2)