ArticleStatistics in medicine2016
Latent class instrumental variables: a clinical and biostatistical perspective.
Article in Statistics in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Meta-analysis of breast cancer mortality benefit and overdiagnosis adjusted for adherence: improving information on the effects of attending screening mammography.British journal of cancer · 2016Pooled it
- Limited versus Extended Pelvic Lymph Node Dissection for Prostate Cancer: A Randomized Clinical Trial.European urology oncology · 2021Trial
- Local average treatment effects with binary outcomes.American journal of epidemiology · 2025Article
- Design and rationale of penn medicine healthy heart, a randomized trial of effectiveness of a centrally organized approach to blood pressure and cholesterol improvement among patients at elevated risk of atherosclerotic cardiovascular disease.American heart journal · 2024Article
- Comments on "sensitivity of estimands in clinical trials with imperfect compliance" by Chen and Heitjan.The international journal of biostatistics · 2024Article
- Multiple discoveries in causal inference: LATE for the party.Chance (New York, N.Y.) · 2024Article
- Instrumental variables methods reconcile intention-to-screen effects across pragmatic cancer screening trials.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Assessing complier average causal effects from longitudinal trials with multiple endpoints and treatment noncompliance: An application to a study of Arthritis Health Journal.Statistics in medicine · 2022Article
- Instrumental variable estimation of early treatment effect in randomized screening trials.Lifetime data analysis · 2021Article
- A Bayesian Hierarchical CACE Model Accounting for Incomplete Noncompliance With Application to a Meta-analysis of Epidural Analgesia on Cesarean Section.Journal of the American Statistical Association · 2021Article
- Latent class instrumental variables and the monotonicity assumption.Emerging themes in epidemiology · 2020Article
- Maximum likelihood estimation with missing outcomes: From simplicity to complexity.Statistics in medicine · 2019Article
- Five criteria for using a surrogate endpoint to predict treatment effect based on data from multiple previous trials.Statistics in medicine · 2018Article
- Editorial: Challenges in Quantifying Overdiagnosis.Journal of the National Cancer Institute · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
Abstract
In some two-arm randomized trials, some participants receive the treatment assigned to the other arm as a result of technical problems, refusal of a treatment invitation, or a choice of treatment in an encouragement design. In some before-and-after studies, the availability of a new treatment changes from one time period to this next. Under assumptions that are often reasonable, the latent class instrumental variable (IV) method estimates the effect of treatment received in the aforementioned scenarios involving all-or-none compliance and all-or-none availability. Key aspects are four initial latent classes (sometimes called principal strata) based on treatment received if in each randomization group or time period, the exclusion restriction assumption (in which randomization group or time period is an instrumental variable), the monotonicity assumption (which drops an implausible latent class from the analysis), and the estimated effect of receiving treatment in one latent class (sometimes called efficacy, the local average treatment effect, or the complier average causal effect). Since its independent formulations in the biostatistics and econometrics literatures, the latent class IV method (which has no well-established name) has gained increasing popularity. We review the latent class IV method from a clinical and biostatistical perspective, focusing on underlying assumptions, methodological extensions, and applications in our fields of obstetrics and cancer research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.