Dear users, I need to estimate a maximum likelihood model with wild bootstrap as I have few cluster issue. I wonder if I can get any advice on how to implement the wild boostrap. To be specific, I did the following to use boottest and failed.
ml model lf ML_eut_mu (CRRA: choice p0b p1b pay0b pay1b = post trt postxtrt ///
) (mu: = )
ml max, diff iterate(100)
boottest postxtrt
Thank you!
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