English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

The instrumental variable method is widely used in the health and socialsciences for identification and estimation of causal effects in the presence ofpotentially unmeasured confounding. In order to improve efficiency, multipleinstruments are routinely used, leading to concerns about bias due to possibleviolation of the instrumental variable assumptions. To address this concern, weintroduce a new class of g-estimators that are guaranteed to remain consistentand asymptotically normal for the causal effect of interest provided that a setof at least $\gamma$ out of $K$ candidate instruments are valid, for$\gamma\leq K$ set by the analyst ex ante, without necessarily knowing theidentities of the valid and invalid instruments. We provide formalsemiparametric efficiency theory supporting our results. Both simulationstudies and applications to the UK Biobank data demonstrate the superiorempirical performance of our estimators compared to competing methods.

Semiparametric Efficient G-estimation with Invalid Instrumental Variables