Cover Image

When do composite estimands answer non-causal questions?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kahan, Brennan C, Pham, Tra My, Tweed, Conor, Morris, Tim P
Format:	Preprint
Published:	2025
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tools to help patients and other stakeholders' input into choice of estimand and intercurrent event strategy in randomised trials
by: Hindley, Joanna, et al.
Published: (2026)

Demystifying estimands in cluster-randomised trials
by: Kahan, Brennan C, et al.
Published: (2023)

On the permutation equivariance principle for causal estimands
by: Tong, Jiaqi, et al.
Published: (2025)

What is estimated in cluster randomized crossover trials with informative sizes? -- A survey of estimands and common estimators
by: Lee, Kenneth M., et al.
Published: (2025)

Absolute average and median treatment effects as causal estimands on metric spaces
by: Shin, Ha-Young, et al.
Published: (2024)

On estimands in target trial emulation
by: Gervasoni, Edoardo Efrem, et al.
Published: (2026)

Semiparametric principal stratification analysis beyond monotonicity
by: Tong, Jiaqi, et al.
Published: (2025)

The ideal trial: defining causal estimands that balance relevance and feasibility in target trial emulations and actual randomized trials
by: Moreno-Betancur, Margarita, et al.
Published: (2024)

When exposure affects subgroup membership: Framing relevant causal questions in perinatal epidemiology and beyond
by: Gupta, Shalika, et al.
Published: (2024)

Model-robust standardization in cluster-randomized trials
by: Li, Fan, et al.
Published: (2025)

Transportability of model-based estimands in evidence synthesis
by: Remiro-Azócar, Antonio
Published: (2022)

Evaluating Informative Cluster Size in Cluster Randomized Trials
by: Blette, Bryan S., et al.
Published: (2025)

Risk-based decision making: estimands for sequential prediction under interventions
by: Luijken, Kim, et al.
Published: (2023)

The purpose of an estimator is what it does: Misspecification, estimands, and over-identification
by: Andrews, Isaiah, et al.
Published: (2025)

Exponentially weighted estimands and the exponential family: Filtering, prediction and smoothing
by: van Heel, Simon Donker, et al.
Published: (2025)

Causal estimands and identification of time-varying effects in non-stationary time series from N-of-1 mobile device data
by: Cai, Xiaoxuan, et al.
Published: (2024)

Effect modification and non-collapsibility leads to conflicting treatment decisions: a review of marginal and conditional estimands and recommendations for decision-making
by: Phillippo, David M., et al.
Published: (2024)

The role of post intercurrent event data in the estimation of hypothetical estimands in clinical trials
by: Bartlett, Jonathan W., et al.
Published: (2025)

Everything all at once: On choosing an estimand for multi-component environmental exposures
by: Rudolph, Kara E., et al.
Published: (2025)

Causal inference and racial bias in policing: New estimands and the importance of mobility data
by: Huang, Zhuochao, et al.
Published: (2024)

When are time series predictions causal? The potential system and dynamic causal effects
by: Carlson, Jacob, et al.
Published: (2026)

Illustrating implications of misaligned causal questions and statistics in settings with competing events and interest in treatment mechanisms
by: Kawahara, Takuya, et al.
Published: (2025)

Inference with weights: Residualization produces short, valid intervals for varying estimands and varying resampling processes
by: Hartman, Erin, et al.
Published: (2025)

Doubly robust estimators of the restricted mean time in favor estimands in individual- and cluster-randomized trials
by: Fang, Xi, et al.
Published: (2026)

Prediction meets causal inference: the role of treatment in clinical prediction models
by: van Geloven, Nan, et al.
Published: (2020)

How should parallel cluster randomized trials with a baseline period be analyzed? A survey of estimands and common estimators
by: Lee, Kenneth Menglin, et al.
Published: (2024)

Pulling back the curtain: the road from statistical estimand to machine-learning based estimator for epidemiologists (no wizard required)
by: Renson, Audrey, et al.
Published: (2025)

How to interpret hazard ratios
by: Bartlett, Jonathan W., et al.
Published: (2026)

Calibration of answer probabilities in verbal autopsies: Working Paper
by: Higgins, Nathan, et al.
Published: (2025)

Joint estimation of insurance loss development factors using Bayesian hidden Markov models
by: Goold, Conor
Published: (2024)

A fully Bayesian approach for the imputation and analysis of derived outcome variables with missingness
by: Campbell, Harlan, et al.
Published: (2024)

Bounding causal effects with an unknown mixture of informative and non-informative missingness
by: Rubinstein, Max, et al.
Published: (2024)

Bounds on causal effects in $2^{K}$ factorial experiments with non-compliance
by: Blackwell, Matthew, et al.
Published: (2024)

Robust Bayesian causal estimation for causal inference in medical diagnosis
by: Basu, Tathagata, et al.
Published: (2024)

Living forwards or understanding backwards? A comparison of Inverse Probability of Treatment Weighting and G-estimation methods for targeting hypothetical full adherence estimands in longitudinal cohort studies
by: Liang, Xiaoran, et al.
Published: (2026)

Identifiability of causal effects with non-Gaussianity and auxiliary covariates
by: Shuai, Kang, et al.
Published: (2023)

Evaluating treatment effects on longitudinal outcomes with attrition due to death: Methods for a two-dimentional estimand with a case study in Quality of Life
by: Reynders, Dries, et al.
Published: (2025)

Bounds for causal mediation effects
by: Breum, Marie S., et al.
Published: (2025)

Revealing the Truth: Calculating True Values in Causal Inference Simulation Studies via Gaussian Quadrature
by: Ocampo, Alex, et al.
Published: (2026)

Misspecifications in structural equation modeling: The choice of latent variables, causal-formative constructs or composites
by: Bauer, Jonas, et al.
Published: (2025)