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Related papers: Principal Stratum Strategy: Potential Role in Drug…

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Principal stratification is a popular framework for causal inference in the presence of an intermediate outcome. While the principal average treatment effects are the standard target of inference, they may be insufficient when interest lies…

Methodology · Statistics 2025-12-29 Xinyuan Chen , Fan Li

Randomized controlled trials are considered the gold standard to evaluate the treatment effect (estimand) for efficacy and safety. According to the recent International Council on Harmonisation (ICH)-E9 addendum (R1), intercurrent events…

Methodology · Statistics 2021-11-24 Junxiang Luo , Stephen J. Ruberg , Yongming Qu

Randomized trials typically estimate average relative treatment effects, but decisions on the benefit of a treatment are possibly better informed by more individualized predictions of the absolute treatment effect. In case of a binary…

Methodology · Statistics 2021-08-20 J Hoogland , J IntHout , M Belias , MM Rovers , RD Riley , FE Harrell , KGM Moons , TPA Debray , JB Reitsma

Time-to-event estimands are central to many oncology clinical trials. The estimand framework (addendum to the ICH E9 guideline) calls for precisely defining the treatment effect of interest to align with the clinical question of interest…

Applications · Statistics 2023-07-24 Jonathan Siegel , Hans-Jochen Weber , Stefan Englert , Feng Liu

In the context of having an instrumental variable, the standard practice in causal inference begins by targeting an effect of interest and proceeds by formulating assumptions enabling its identification. We turn this around by adhering to…

Statistics Theory · Mathematics 2026-05-25 Carlos García Meixide , Mark J. van der Laan

Randomized trials are considered the gold standard for making informed decisions in medicine, yet they often lack generalizability to the patient populations in clinical practice. Observational studies, on the other hand, cover a broader…

Methodology · Statistics 2026-04-14 Piersilvio De Bartolomeis , Javier Abad , Konstantin Donhauser , Fanny Yang

The regression discontinuity (RD) design is a quasi-experimental design that estimates the causal effects of a treatment by exploiting naturally occurring treatment rules. It can be applied in any context where a particular treatment or…

The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) E9 (R1) Addendum provides a framework for defining estimands in clinical trials. Treatment policy strategy is the mostly used…

Applications · Statistics 2024-10-10 Rong Liu , Yongming Qu

The estimand framework provides guidance on handling intercurrent events, such as treatment discontinuation, in the analysis of clinical trial responses. Under ICH E9(R1), the treatment policy (TP) strategy incorporates post-discontinuation…

Methodology · Statistics 2026-04-07 Myeongjong Kang , Sangyoon Yi

Average and conditional treatment effects are fundamental causal quantities used to evaluate the effectiveness of treatments in various critical applications, including clinical settings and policy-making. Beyond the gold-standard…

A platform trial is an innovative clinical trial design that uses a master protocol to evaluate multiple treatments, where patients are often assigned to different subsets of treatment arms based on individual characteristics, enrollment…

We develop a Bayesian nonparametric (BNP) approach to evaluate the causal effect of treatment in a randomized trial where a nonterminal event may be censored by a terminal event, but not vice versa (i.e., semi-competing risks). Based on the…

Methodology · Statistics 2019-07-23 Yanxun Xu , Daniel Scharfstein , Peter Müller , Michael Daniels

For obtaining causal inferences that are objective, and therefore have the best chance of revealing scientific truths, carefully designed and executed randomized experiments are generally considered to be the gold standard. Observational…

Applications · Statistics 2008-11-12 Donald B. Rubin

Researchers are frequently interested in understanding the causal effect of treatment interventions. However, in some cases, the treatment of interest--readily available in a randomized controlled trial (RCT)--is either not directly…

Methodology · Statistics 2025-09-29 Lan Wen , Aaron L Sarvet

It is a common practice in randomized clinical trials with the standard survival outcome to follow patients until a prespecified number of events have been observed, a type of trial known as the event-driven trial. The event-driven design…

Methodology · Statistics 2026-02-10 Jingwen Zhang , Satoshi Hattori

Randomized experiments are widely used to estimate causal effects across a variety of domains. However, classical causal inference approaches rely on critical independence assumptions that are violated by network interference, when the…

Methodology · Statistics 2022-10-18 Mayleen Cortez , Matthew Eichhorn , Christina Lee Yu

Typically, a randomized experiment is designed to test a hypothesis about the average treatment effect and sometimes hypotheses about treatment effect variation. The results of such a study may then be used to inform policy and practice for…

Methodology · Statistics 2026-05-01 Elizabeth Tipton , Michalis Mamakos

Interference occurs when the potential outcomes of a unit depend on the treatment of others. Interference can be highly heterogeneous, where treating certain individuals might have a larger effect on the population's overall outcome. A…

Methodology · Statistics 2025-04-11 Samantha G Dean , Georgia Papadogeorgou , Laura Forastiere

Many public health interventions are conducted in settings where individuals are connected to one another and the intervention assigned to randomly selected individuals may spill over to other individuals they are connected to. In these…

Methodology · Statistics 2026-01-14 Junhan Fang , Donna Spiegelman , Ashley Buchanan , Laura Forastiere

Time-to-event endpoints are central to evaluate treatment efficacy across many disease areas. Many trial protocols include interim analyses within group-sequential designs that control type I error via spending functions or boundary…

Methodology · Statistics 2026-01-19 Edoardo Ratti , Federico L. Perlino , Stefania Galimberti , Maria G. Valsecchi