Comments on “sensitivity of estimands in clinical trials with imperfect compliance” by Chen and Heitjan
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Abstract
Chen and Heitjan (Sensitivity of estimands in clinical trials with imperfect compliance. Int J Biostat. 2023) used linear extrapolation to estimate the population average causal effect (PACE) from the complier average causal effect (CACE) in multiple randomized trials with all-or-none compliance. For extrapolating from CACE to PACE in this setting and in the paired availability design involving different availabilities of treatment among before-and-after studies, we recommend the sensitivity analysis in Baker and Lindeman (J Causal Inference, 2013) because it is not restricted to a linear model, as it involves various random effect and trend models.
Funding source: Division of Cancer Prevention, National Cancer Institute
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Research ethics: Not applicable.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Not applicable.
References
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Artikel in diesem Heft
- Frontmatter
- Research Articles
- Random forests for survival data: which methods work best and under what conditions?
- Flexible variable selection in the presence of missing data
- An interpretable cluster-based logistic regression model, with application to the characterization of response to therapy in severe eosinophilic asthma
- MBPCA-OS: an exploratory multiblock method for variables of different measurement levels. Application to study the immune response to SARS-CoV-2 infection and vaccination
- Detecting differentially expressed genes from RNA-seq data using fuzzy clustering
- Hypothesis testing for detecting outlier evaluators
- Response to comments on ‘sensitivity of estimands in clinical trials with imperfect compliance’
- Commentary
- Comments on “sensitivity of estimands in clinical trials with imperfect compliance” by Chen and Heitjan
- Research Articles
- Optimizing personalized treatments for targeted patient populations across multiple domains
- Statistical models for assessing agreement for quantitative data with heterogeneous random raters and replicate measurements
- History-restricted marginal structural model and latent class growth analysis of treatment trajectories for a time-dependent outcome
- Revisiting incidence rates comparison under right censorship
- Ensemble learning methods of inference for spatially stratified infectious disease systems
- The survival function NPMLE for combined right-censored and length-biased right-censored failure time data: properties and applications
- Hybrid classical-Bayesian approach to sample size determination for two-arm superiority clinical trials
- Estimation of a decreasing mean residual life based on ranked set sampling with an application to survival analysis
- Improving the mixed model for repeated measures to robustly increase precision in randomized trials
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- Kalman filter with impulse noised outliers: a robust sequential algorithm to filter data with a large number of outliers
- Bayesian estimation and prediction for network meta-analysis with contrast-based approach
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