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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국자료분석학회 Journal of The Korean Data Analysis Society Journal of The Korean Data Analysis Society 제22권 제5호
- 발행연도
- 2020.1
- 수록면
- 1,707 - 1,720 (14page)
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초록· 키워드
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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
등록된 정보가 없습니다.
참고문헌 (22)
참고문헌 신청
Bernal, J. L. / 2016 / Interrupted time series regression for the evaluation of public health interventions : A tutorial / International Journal of Epidemiology 46:348~355
Chinn S. / 2000 / A simple method for converting an odds ratio to effect size for use in meta-analysis / Statistics in medicine 19(22):3127~3131
Donner, A. / 1981 / Randomization by cluster, Sample size requirements and analysis / American journal of epidemiology 114(6):906~914
Foy, R. / 2011 / A cluster randomised trial of educational messages to improve the primary care of diabetes, Implementation science / IS 6:129
Fretheim, A. / 2013 / Interrupted time-series analysis yielded an effect estimate concordant with the cluster-randomized controlled trial result / Journal of Clinical Epidemiology 66(8):883~887
Chinn S. / 2000 / A simple method for converting an odds ratio to effect size for use in meta-analysis / Statistics in medicine 19(22):3127~3131
Donner, A. / 1981 / Randomization by cluster, Sample size requirements and analysis / American journal of epidemiology 114(6):906~914
Foy, R. / 2011 / A cluster randomised trial of educational messages to improve the primary care of diabetes, Implementation science / IS 6:129
Fretheim, A. / 2013 / Interrupted time-series analysis yielded an effect estimate concordant with the cluster-randomized controlled trial result / Journal of Clinical Epidemiology 66(8):883~887
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