如何决定我是否需要在 R 的回归中使用权重

Question

I have a dataset which is a combination of some survey results and some demographics. All survey results are normalized by population density. Now I want to design a model to see the relationship between some of the variables. The model looks like this:

lm(log(violation+1) ~ Wighted.mean + mks + In_ct + Asian + Black + Hispanic + PopDen + MedHouseIncome, data = dt, weights = pop)

How can I decide if weights is useful here? When I remove it I get different coefficients with less R-square. But I feel like that is not enough to decide. Can anyone give me suggestions of how to decide that?

Answer 1

使用 summary(m.lm) 并使用最小估计值（f.ex. <10% 的可变性）和最高 Pr(>|t|) 值（f.ex. > 0.05）删除权重。