What type of study is this?

This is a Quantitative Study study.

October 1, 2025Open Access

Intra-Class Correlation Coefficient Ignorable Clustered Randomized Trials for Detecting Treatment Effect Heterogeneity

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Authors

YCYang ChenUniversity of Electronic Science and Technology of China MDMárcio A. DinizCedars-Sinai Medical Center DKDeukwoo KwonUniversity of Arkansas for Medical Sciences

Discussion

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Implication

This approach allows for calculating sample size without considering intra-class correlation, suggesting improvements for trials facing design challenges.

Key Points

The study shows that treatment effect heterogeneity can be detected without estimating the intra-class correlation coefficient.
Power calculations in clustered randomized trials are sensitive to ICC assumptions, impacting trial feasibility and costs.
This theoretical foundation provides a novel framework for ICC-ignorable clustered randomized trials, enhancing practical applications.
Improving power can be achieved by expanding cluster sizes instead of increasing the number of clusters required for trials.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/68dd91c7fe798ba2fc49854e https://doi.org/10.48550/arxiv.2504.15503

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October 1, 2025Open Access

Intra-Class Correlation Coefficient Ignorable Clustered Randomized Trials for Detecting Treatment Effect Heterogeneity

View Full Paper

Ask AI

Bookmark

Authors

YCYang ChenUniversity of Electronic Science and Technology of China MDMárcio A. DinizCedars-Sinai Medical Center DKDeukwoo KwonUniversity of Arkansas for Medical Sciences

Discussion

Member takes

Implication

This approach allows for calculating sample size without considering intra-class correlation, suggesting improvements for trials facing design challenges.

Key Points

The study shows that treatment effect heterogeneity can be detected without estimating the intra-class correlation coefficient.
Power calculations in clustered randomized trials are sensitive to ICC assumptions, impacting trial feasibility and costs.
This theoretical foundation provides a novel framework for ICC-ignorable clustered randomized trials, enhancing practical applications.
Improving power can be achieved by expanding cluster sizes instead of increasing the number of clusters required for trials.

Cite This Study

Chen et al. (2025) studied this question.

synapsesocial.com/papers/68dd91c7fe798ba2fc49854e https://doi.org/10.48550/arxiv.2504.15503

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