Run a regression with omitted category

I have a dataset like these

BirthYear walking
50-70 500
70-90 700
90-10 200
70-90 450
70-90 850
70-90 890
30-50 660
70-90 760
70-90 450
30-50 230
30-50 120
50-70 120
70-90 340
90-10 920

I want to run a regression of walking on BirthYear and that the BirthYear 90-10 is the omitted category, to find out how much 70-90 people walk less than 90-10 people on average.

I gave this code but don’t know how to fix with omitted category for 90-10.

feols(fml = walking ~ BirthYear, data = df)

>Solution :

To put the 70-90 category in the reference/intercept simply use the relevel function

> df$BirthYear=factor(df$BirthYear)
> df$BirthYear=relevel(df$BirthYear,"70-90")
> summary(lm(walking~BirthYear,data=df))

Coefficients:
               Estimate Std. Error t value Pr(>|t|)    
(Intercept)      634.29     105.62   6.006 0.000131 ***
BirthYear30-50  -297.62     192.83  -1.543 0.153754    
BirthYear50-70  -324.29     224.05  -1.447 0.178396    
BirthYear90-10   -74.29     224.05  -0.332 0.747062

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