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학술논문

Piecewise Logistic Regression for Cluster Randomized Controlled Trial of Health System Interventions

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영문명
발행기관
한국자료분석학회
저자명
Seo Young Park
간행물 정보
『Journal of The Korean Data Analysis Society (JKDAS)』Vol.22 No.5, 1707~1720쪽, 전체 14쪽
주제분류
자연과학 > 통계학
파일형태
PDF
발행일자
2020.10.30
4,480

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영문 초록

In cluster randomized controlled trials (CRCT) of health system interventions, the distribution of primary outcome is often changing over time due to events external to the intervention. We introduce piecewise logistic regression model to tease out the effect of the intervention given ongoing background change in outcome distribution. Using simulation, we estimated the power of the model and compared it with the power of the controlled interrupted time series (ITS) analysis method. We randomly generated datasets under various scenarios to estimate the power. We considered a range of sample size and cases where the effect size was small, medium, and large. The piecewise logistic regression model had adequate power to detect intervention effects when the true intervention effect was medium or high. When the true intervention effect was small, the model still had reasonable power depending on the sample size. The power of piecewise logistic regression model was greater than or comparable to that of the controlled ITS analysis. Piecewise logistic regression is a useful method to analyze repeated cross-sectional binary outcomes from CRCT of health system interventions. The result of this study can be used for designing RCTs of health system interventions.

목차

1. Background
2. Methods
3. Results
4. Discussion
5. Conclusion
References

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APA

Seo Young Park. (2020).Piecewise Logistic Regression for Cluster Randomized Controlled Trial of Health System Interventions. Journal of The Korean Data Analysis Society (JKDAS), 22 (5), 1707-1720

MLA

Seo Young Park. "Piecewise Logistic Regression for Cluster Randomized Controlled Trial of Health System Interventions." Journal of The Korean Data Analysis Society (JKDAS), 22.5(2020): 1707-1720

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