Description
Computes the implied weights of linear regression models for estimating
average causal effects and provides diagnostics based on these weights. These
diagnostics rely on the analyses in Chattopadhyay and Zubizarreta (2023)
where
several regression estimators are represented as weighting estimators, in connection
to inverse probability weighting. 'lmw' provides tools to diagnose
representativeness, balance, extrapolation, and influence for these models,
clarifying the target population of inference. Tools are also available to
simplify estimating treatment effects for specific target populations of interest.