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Critical assessment of intent-to-treat analyses
Open accessAbstract
SUMMARYRandomised clinical trial (RCT) is considered by many to be the gold standard in cost-effectiveness studies, as one is able to balance confounding factors by the procedure of randomisation. In many cases, intent-to-treat analysis (ITT) is preferred over other approaches in handling RCT data, for its extensive inclusion of all study subjects and complete collection of cost data. However, in situations where there are a large amount of drop-out subjects, it is necessary to consider other analytical methods together with ITT. Per-protocol analysis (PP) and as-treated analysis (AT) are two frequent options. PP only includes subjects with sufficient compliance to treatment, while AT categorises patients not only by treatment but also by compliance status. In real practice, scientists should balance the pros and cons of these methods and appropriately apply them to achieve maximum study validity.
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Non-compliers might have certain characteristics that differ from compliers that would impact the effect of treatment, and non-compliance might be higher in the treatment condition than in the control condition, violating the goal of random assignment.
“Non-compliers might have certain characteristics that differ from compliers that would impact the effect of treatment (Shaya & Gu, 2007) and non-compliance might be higher in the treatment condition than in the control condition, violating the goal of random assignment.”
From Do growth mindset interventions impact students’ academic achievement? A systematic review and meta-analysis with recommendations for best practices. (2023) · cites this paper as Shaya & Gu, 2007
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Cites
Statistical Considerations in the Intent-to-Treat Principle
Lachin, J. M. (2000) · Controlled Clinical Trials · doi:10.1016/s0197-2456(00)00046-5 · Cited by 652
Controversy in Counting and Attributing Events in Clinical Trials
Sackett, D. L., & Gent, M. (1979) · New England Journal of Medicine · doi:10.1056/nejm197912273012602 · Cited by 413
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Research works printed but not linked: 5
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Macnamara, B. N., & Burgoyne, A. P. (2023) · Psychological Bulletin · doi:10.1037/bul0000352 · Cited by 415
Metadata
- Authors
- Shaya, F. T., & Gu, A.
- Venue
- Journal of Medical Economics
- Publisher
- Informa Healthcare
- Published
- 2007-01
- Volume
- 10
- Issue
- 2
- Pages
- 171-177
- ISSN
- 1369-6998 (ISSN-L)
- 1941-837X
- OpenAlex
- W2120776530
- Cited by
- 8
- References
- 2
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 1 · 2019: 2 · 2017: 1
- FWCI
- 0.00
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Medical Economics (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Keywords
- intention-to-treat analysis, per-protocol analysis, as-treated analysis, randomized controlled trials, cost-effectiveness analysis, treatment discontinuation, medication adherence, research validity
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