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Propensity score matching (PSM) and regression adjustment for causal inference in non-randomized studies with health-related quality of life (HRQoL) outcomes

Abstract:
We investigate the performance of propensity score matching (PSM) and multiple linear regression (MLR), both individually or combined, on simulated non-randomized Health Related Quality of Life (HRQoL) data. We examine whether the combined use of propensity score matching with multiple linear regression adjustment (PSMRA) produces more reliable estimates of the average treatment effect on the treated (ATT), than those obtained using either PSM or MLR alone.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s11136-016-1390-7

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Institution:
University of Oxford
Division:
MSD
Department:
NDORMS
Sub department:
Centre for Statistics in Medicine
Role:
Author
ORCID:
0000-0002-2772-2316
Publisher:
Springer Publisher's website
Journal:
23rd Annual Conference of the International Society for Quality of Life Research (ISOQOL 2016) Journal website
Host title:
23rd Annual Conference of the International Society for Quality of Life Research (ISOQOL 2016)
Publication date:
2016-09-20
Acceptance date:
2016-06-01
DOI:
Source identifiers:
720947
Pubs id:
pubs:720947
UUID:
uuid:83750d87-671b-4ebb-b78c-c3fb533d171c
Local pid:
pubs:720947
Deposit date:
2018-05-31

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