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Currently the error for lmtp_contrast when using lmtp_sub or lmtp_ipw objects is that lmtp_contrast is not implemented for these estimators. It may be helpful to elaborate that this is purposeful, since we do not have any asymptotic linearity theory to support SEs from these estimators when ensemble learning is used. Also, maybe an explicit recommendation that "the authors of lmtp recommend using the tmle or sdr estimation methods for optimal results" would be good? Perhaps a reference would be helpful, too. Right now I can only think of Sherri Rose's Intro to TMLE paper as a good ref for an approachable explanation of the cons of IPW/G comp, but there's probably other good ones! https://academic.oup.com/aje/article/185/1/65/2662306
The text was updated successfully, but these errors were encountered:
Currently the error for
lmtp_contrast
when usinglmtp_sub
orlmtp_ipw
objects is thatlmtp_contrast
is not implemented for these estimators. It may be helpful to elaborate that this is purposeful, since we do not have any asymptotic linearity theory to support SEs from these estimators when ensemble learning is used. Also, maybe an explicit recommendation that "the authors of lmtp recommend using the tmle or sdr estimation methods for optimal results" would be good? Perhaps a reference would be helpful, too. Right now I can only think of Sherri Rose's Intro to TMLE paper as a good ref for an approachable explanation of the cons of IPW/G comp, but there's probably other good ones! https://academic.oup.com/aje/article/185/1/65/2662306The text was updated successfully, but these errors were encountered: