Proximal indirect comparison
We consider the problem of indirect comparison, where a treatment arm of interest is absent by design in the target randomized control trial (RCT) but available in a source RCT. The identifiability of the target population average treatment effect often relies on conditional transportability assumpt...
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| creator | Su, Zehao Rytgaard, Helene C. W Ravn, Henrik Eriksson, Frank |
| description | We consider the problem of indirect comparison, where a treatment arm of
interest is absent by design in the target randomized control trial (RCT) but
available in a source RCT. The identifiability of the target population average
treatment effect often relies on conditional transportability assumptions.
However, it is a common concern whether all relevant effect modifiers are
measured and controlled for. We highlight a new proximal identification result
in the presence of shifted, unobserved effect modifiers based on proxies: an
adjustment proxy in both RCTs and an additional reweighting proxy in the source
RCT. We propose an estimator which is doubly-robust against misspecifications
of the so-called bridge functions and asymptotically normal under mild
consistency of the nuisance models. An alternative estimator is presented to
accommodate missing outcomes in the source RCT, which we then apply to conduct
a proximal indirect comparison analysis using two weight management trials. |
| doi_str_mv | 10.48550/arxiv.2405.10773 |
| format | Article |
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interest is absent by design in the target randomized control trial (RCT) but
available in a source RCT. The identifiability of the target population average
treatment effect often relies on conditional transportability assumptions.
However, it is a common concern whether all relevant effect modifiers are
measured and controlled for. We highlight a new proximal identification result
in the presence of shifted, unobserved effect modifiers based on proxies: an
adjustment proxy in both RCTs and an additional reweighting proxy in the source
RCT. We propose an estimator which is doubly-robust against misspecifications
of the so-called bridge functions and asymptotically normal under mild
consistency of the nuisance models. An alternative estimator is presented to
accommodate missing outcomes in the source RCT, which we then apply to conduct
a proximal indirect comparison analysis using two weight management trials.</description><identifier>DOI: 10.48550/arxiv.2405.10773</identifier><language>eng</language><subject>Statistics - Methodology</subject><creationdate>2024-05</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,776,881</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2405.10773$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2405.10773$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Su, Zehao</creatorcontrib><creatorcontrib>Rytgaard, Helene C. W</creatorcontrib><creatorcontrib>Ravn, Henrik</creatorcontrib><creatorcontrib>Eriksson, Frank</creatorcontrib><title>Proximal indirect comparison</title><description>We consider the problem of indirect comparison, where a treatment arm of
interest is absent by design in the target randomized control trial (RCT) but
available in a source RCT. The identifiability of the target population average
treatment effect often relies on conditional transportability assumptions.
However, it is a common concern whether all relevant effect modifiers are
measured and controlled for. We highlight a new proximal identification result
in the presence of shifted, unobserved effect modifiers based on proxies: an
adjustment proxy in both RCTs and an additional reweighting proxy in the source
RCT. We propose an estimator which is doubly-robust against misspecifications
of the so-called bridge functions and asymptotically normal under mild
consistency of the nuisance models. An alternative estimator is presented to
accommodate missing outcomes in the source RCT, which we then apply to conduct
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interest is absent by design in the target randomized control trial (RCT) but
available in a source RCT. The identifiability of the target population average
treatment effect often relies on conditional transportability assumptions.
However, it is a common concern whether all relevant effect modifiers are
measured and controlled for. We highlight a new proximal identification result
in the presence of shifted, unobserved effect modifiers based on proxies: an
adjustment proxy in both RCTs and an additional reweighting proxy in the source
RCT. We propose an estimator which is doubly-robust against misspecifications
of the so-called bridge functions and asymptotically normal under mild
consistency of the nuisance models. An alternative estimator is presented to
accommodate missing outcomes in the source RCT, which we then apply to conduct
a proximal indirect comparison analysis using two weight management trials.</abstract><doi>10.48550/arxiv.2405.10773</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Statistics - Methodology |
| title | Proximal indirect comparison |
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