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/

Global: Zendy Plus annual

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

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

When comparing time-varying treatments in a non-randomised setting, one mustoften correct for time-dependent confounders that influence treatment choiceover time and that are themselves influenced by treatment. We present a new twostep procedure, based on additive hazard regression and linear incrementsmodels, for handling such confounding when estimating average treatment effectson the treated (ATT). The approach can also be used for mediation analysis. Themethod is applied to data from the Swiss HIV Cohort Study, estimating theeffect of antiretroviral treatment on time to AIDS or death. Compared to othermethods for estimating the ATT, the proposed method is easy to implement usingavailable software packages in R.

Estimating the treatment effect on the treated under time-dependent confounding in an application to the Swiss HIV Cohort Study