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) <doi:10.1093/biomet/asac058> 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.
Package details |
|
---|---|
Author | Ambarish Chattopadhyay [aut] (<https://orcid.org/0000-0002-1502-0974>), Noah Greifer [aut, cre] (<https://orcid.org/0000-0003-3067-7154>), Jose Zubizarreta [aut] (<https://orcid.org/0000-0002-0322-147X>) |
Maintainer | Noah Greifer <ngreifer@iq.harvard.edu> |
License | GPL (>= 2) |
Version | 0.0.2 |
URL | https://github.com/ngreifer/lmw |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.