One weird trick for better inference in experimental designs
Austin Nichols
Additional contact information
Austin Nichols: Abt Associates
2021 Stata Conference from Stata Users Group
Abstract:
A long line of research debates the merits of statistical adjustment for baseline or pretreatment characteristics for random assignment designs (Fisher 1935; Freedman 2008a, 2008b; Lin 2013; Kallus 2018). A related literature explores better methods to conduct statistical adjustment for potential confounders in nonexperimental designs. This presentation presents the results of a simulation showing large potential improvements in inference for random assignment designs attainable using commands designed to adjust for potential confounders newly available in Stata 16.
Date: 2021-08-07
References: Add references at CitEc
Citations:
Downloads: (external link)
http://fmwww.bc.edu/repec/scon2021/US21_Nicols.pdf
Our link check indicates that this URL is bad, the error code is: 404 Not Found
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:boc:scon21:9
Access Statistics for this paper
More papers in 2021 Stata Conference from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().