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!
Related Posts with Wild bootstrap with ML
difference in proportionsHello, Having a daft moment. I surveyed 2006 respondents about cats. 1002 were Urban and 1004 rural…
calculating sd using rolling windowDear colleagues I have monthly return data and I wanted to calculate a rolling 3 year SD using mont…
Trying to label multiple variables using loopHi all, I am trying to label multiple variables at once using loop. For instance, variables q2_4_1…
Help Responding to Critique that Adjusted Wald F Test is not Appropriate for Weighted Examination of Change over Time in ProportionsI need to respond to a reviewer's critique of my use of an adjusted Wald F Test (extension of McNema…
Using -asdoc- to export a local -matrix-Dear Statalisters, I want to export regression results in a neat table. I am using a -matrix- to ex…
Subscribe to:
Post Comments (Atom)
0 Response to Wild bootstrap with ML
Post a Comment