Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

scientific article published on 5 October 2015

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies? is …
instance of (P31):
scholarly articleQ13442814

External links are
P356DOI10.2217/CER.15.23
P698PubMed publication ID26436848

P2093author name stringNilay Shah
Bijan Borah
Jason Swindle
Melvin Olson
Jessica Chang
William Crown
Paul Buzinec
Kristijan Kahler
P2860cites workThe prevalence of hepatitis C virus infection in the United States, 1999 through 2002Q29619974
Ignoring dependency between linking variables and its impact on the outcome of probabilistic record linkage studies.Q36858961
Peginterferon alfa-2b or alfa-2a with ribavirin for treatment of hepatitis C infectionQ42989510
Some cautions on the use of instrumental variables estimators in outcomes research: how bias in instrumental variables estimators is affected by instrument strength, instrument contamination, and sample size.Q47339336
P433issue5
P921main subjectbiasQ742736
P304page(s)455-463
P577publication date2015-10-05
P1433published inJournal of Comparative Effectiveness ResearchQ22080407
P1476titleCan statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?
P478volume4