Hi, I hope the answer is not too obvious as I am new to Julia.
I want to do some regressions with a weighted sample. At the moment I use the GLM package and I saw there are ProbabilityWeights, but I haven’t figured out how to use them together. Can anybody help?
GLM offers limited support for weights at the moment. The basic usage goes like,
using DataFrames, GLM
srand(0)
df = DataFrame(y = rand(1:10, 10),
x = rand(10),
w = rand(1:10, 10))
glm(@formula(y ~ x), df, Normal(), IdentityLink()) # OLS
glm(@formula(y ~ x), df, Normal(), IdentityLink(),
wts = float.(df[:w])) # WLS
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Thanks, it works smoothely.
Compared to R’s survey package I noticed smaller standard errors. Do you have any idea why?
GLM interprets weights as analytic (a.k.a. inverse variance) weights, like R’s glm
. If you pass it sampling (a.k.a. inverse probability) weights, you’ll get incorrect standard errors.
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