دورية أكاديمية

Sample-constrained partial identification with application to selection bias

التفاصيل البيبلوغرافية
العنوان: Sample-constrained partial identification with application to selection bias
المؤلفون: Matthew J Tudball, Rachael A Hughes, Kate Tilling, Jack Bowden, Qingyuan Zhao
المصدر: Biometrika Trust, Biometrika. 110(2):485-498
سنة النشر: 2023
الوصف: SummaryMany partial identification problems can be characterized by the optimal value of a function over a set where both the function and set need to be estimated by empirical data. Despite some progress for convex problems, statistical inference in this general setting remains to be developed. To address this, we derive an asymptotically valid confidence interval for the optimal value through an appropriate relaxation of the estimated set. We then apply this general result to the problem of selection bias in population-based cohort studies. We show that existing sensitivity analyses, which are often conservative and difficult to implement, can be formulated in our framework and made significantly more informative via auxiliary information on the population. We conduct a simulation study to evaluate the finite sample performance of our inference procedure, and conclude with a substantive motivating example on the causal effect of education on income in the highly selected UK Biobank cohort. We demonstrate that our method can produce informative bounds using plausible population-level auxiliary constraints. We implement this method in the $\texttt{R}$ package $\texttt{selectioninterval}$.
نوع الوثيقة: redif-article
اللغة: English
الإتاحة: https://ideas.repec.org/a/oup/biomet/v110y2023i2p485-498..html
رقم الأكسشن: edsrep.a.oup.biomet.v110y2023i2p485.498.
قاعدة البيانات: RePEc