CODEWITHSUNDEEP
rglm
Jon
Jon

Reputation: 33

Getting the same results for two different models in glm() in RStudio

I'm new to the R tool and am having some trouble with the glm() function. I have some data that I have showed below. When the linear predictor is just x, the glm() function works fine but as soon as I change the linear predictor to x + x^2, it starts giving me the same results that I got for the first model. The code is as follows:

model1 <- glm(y ~ x, data=data1, family=poisson (link="log"))

coef(model1) (Intercept) x 0.3396339 0.2565236

model2 <- glm(y ~ x + x^2, data=data1, family=poisson (link="log"))

coef(model2) (Intercept) x 0.3396339 0.2565236

As you can see there's no coefficient for x^2 as if it's not even in the model.

Upvotes: 1

Views: 276

Answers (1)

CSJCampbell
CSJCampbell

Reputation: 2115

The lm and glm functions have a special interpretation of the formula (see ?formula) which can be confusing if you are not expecting it. The intended usage of the interface is (w + x)^2 means a*w + b*x + c*w*x + d! If you wish to suppress this you need to use the literal function, I.

model2 <- glm(gear ~ disp + I(disp^2), 
    data = mtcars, family = poisson (link = "log"))
coef(model2)
#  (Intercept)          disp     I(disp^2) 
# 1.542059e+00 -1.248689e-03  6.578518e-07

Put another way, I allows you to perform transformations in the call to glm. The following is equivalent.

mtcars1 <- mtcars
mtcars1$disp_sq <- mtcars1$disp^2
model2a <- glm(gear ~ disp + disp_sq, 
    data = mtcars1, family = poisson (link = "log"))
coef(model2a)
#   (Intercept)          disp       disp_sq 
# 1.542059e+00 -1.248689e-03  6.578518e-07

Upvotes: 3

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