{"title":"模拟研究表明,在随机对照试验中,线性回归和Mann-Whitney检验可用于分析存活和在家30天(DAH30)的结果。","authors":"Jonathan Alistair Cook","doi":"10.1016/j.jclinepi.2025.111674","DOIUrl":null,"url":null,"abstract":"<div><h3>Background and Objectives</h3><div>The aims of the work were to consider the properties of the days alive and at home by day 30 (DAH30) from a statistical perspective, and to conduct a simulation study exploring the use of simple (unadjusted) linear regression and Mann-Whitney test as the method of analysis reflect realized analysis options.</div></div><div><h3>Study Design and Setting</h3><div>The days alive and at home by day 30 (DAH30) has been proposed a patient-centric outcome, and clinically relevant outcome suitable for clinical trials. It has unusual statistical properties, and suitability of standard statistical analysis methods is unclear. The properties of DAH30 were reviewed. Simulations based upon 1:1 allocation in an randomized controlled trial (RCT) based upon empirical data were conducted reflecting different additive and realized (reflecting the DAH30) treatment effects, sample sizes and distributions with varying and central locations and zero value level. A variety of metrics were used to assess performance (including bias, coverage, and rejection rate).</div></div><div><h3>Results</h3><div>Linear regression provided a valid estimate of the unadjusted average treatment effect with an additive treatment. This was confirmed in terms of bias, estimation of variance, rejection rate in the absence of an effect, and coverage of the 95% confidence interval for the true realized effect. Mann-Whitney provided greater (power) than linear regression in some situations.</div></div><div><h3>Conclusion</h3><div>Simple linear regression is a reasonable analytic option for the DAH30 for estimating the average treatment effect in the RCT cohort (ie, an intention to treat, or “treatment policy” estimand) where zero-inflation is relatively low. Mann-Whitney test in some circumstances (small effects and smaller samples sizes) provides better ability (like for like) to detect a difference between the groups.</div></div><div><h3>Plain Language Summary</h3><div>Simple linear regression can be used to analyze DAH30 outcome in a randomized trial for a range of scenarios which were considered in this study (including relatively proportions of zero values). The DAH30's properties affect the treatment effect than can be estimated. Mann-Whitney test offered better ability to detect a difference of a smaller magnitude for smaller samples sizes.</div></div>","PeriodicalId":51079,"journal":{"name":"Journal of Clinical Epidemiology","volume":"180 ","pages":"Article 111674"},"PeriodicalIF":7.3000,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A simulation study showed that linear regression and Mann-Whitney test can be used to analyze the days alive and at home by day 30 outcome in a randomized controlled trial\",\"authors\":\"Jonathan Alistair Cook\",\"doi\":\"10.1016/j.jclinepi.2025.111674\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Background and Objectives</h3><div>The aims of the work were to consider the properties of the days alive and at home by day 30 (DAH30) from a statistical perspective, and to conduct a simulation study exploring the use of simple (unadjusted) linear regression and Mann-Whitney test as the method of analysis reflect realized analysis options.</div></div><div><h3>Study Design and Setting</h3><div>The days alive and at home by day 30 (DAH30) has been proposed a patient-centric outcome, and clinically relevant outcome suitable for clinical trials. It has unusual statistical properties, and suitability of standard statistical analysis methods is unclear. The properties of DAH30 were reviewed. Simulations based upon 1:1 allocation in an randomized controlled trial (RCT) based upon empirical data were conducted reflecting different additive and realized (reflecting the DAH30) treatment effects, sample sizes and distributions with varying and central locations and zero value level. A variety of metrics were used to assess performance (including bias, coverage, and rejection rate).</div></div><div><h3>Results</h3><div>Linear regression provided a valid estimate of the unadjusted average treatment effect with an additive treatment. This was confirmed in terms of bias, estimation of variance, rejection rate in the absence of an effect, and coverage of the 95% confidence interval for the true realized effect. Mann-Whitney provided greater (power) than linear regression in some situations.</div></div><div><h3>Conclusion</h3><div>Simple linear regression is a reasonable analytic option for the DAH30 for estimating the average treatment effect in the RCT cohort (ie, an intention to treat, or “treatment policy” estimand) where zero-inflation is relatively low. Mann-Whitney test in some circumstances (small effects and smaller samples sizes) provides better ability (like for like) to detect a difference between the groups.</div></div><div><h3>Plain Language Summary</h3><div>Simple linear regression can be used to analyze DAH30 outcome in a randomized trial for a range of scenarios which were considered in this study (including relatively proportions of zero values). The DAH30's properties affect the treatment effect than can be estimated. Mann-Whitney test offered better ability to detect a difference of a smaller magnitude for smaller samples sizes.</div></div>\",\"PeriodicalId\":51079,\"journal\":{\"name\":\"Journal of Clinical Epidemiology\",\"volume\":\"180 \",\"pages\":\"Article 111674\"},\"PeriodicalIF\":7.3000,\"publicationDate\":\"2025-01-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Clinical Epidemiology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0895435625000071\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Clinical Epidemiology","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0895435625000071","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
A simulation study showed that linear regression and Mann-Whitney test can be used to analyze the days alive and at home by day 30 outcome in a randomized controlled trial
Background and Objectives
The aims of the work were to consider the properties of the days alive and at home by day 30 (DAH30) from a statistical perspective, and to conduct a simulation study exploring the use of simple (unadjusted) linear regression and Mann-Whitney test as the method of analysis reflect realized analysis options.
Study Design and Setting
The days alive and at home by day 30 (DAH30) has been proposed a patient-centric outcome, and clinically relevant outcome suitable for clinical trials. It has unusual statistical properties, and suitability of standard statistical analysis methods is unclear. The properties of DAH30 were reviewed. Simulations based upon 1:1 allocation in an randomized controlled trial (RCT) based upon empirical data were conducted reflecting different additive and realized (reflecting the DAH30) treatment effects, sample sizes and distributions with varying and central locations and zero value level. A variety of metrics were used to assess performance (including bias, coverage, and rejection rate).
Results
Linear regression provided a valid estimate of the unadjusted average treatment effect with an additive treatment. This was confirmed in terms of bias, estimation of variance, rejection rate in the absence of an effect, and coverage of the 95% confidence interval for the true realized effect. Mann-Whitney provided greater (power) than linear regression in some situations.
Conclusion
Simple linear regression is a reasonable analytic option for the DAH30 for estimating the average treatment effect in the RCT cohort (ie, an intention to treat, or “treatment policy” estimand) where zero-inflation is relatively low. Mann-Whitney test in some circumstances (small effects and smaller samples sizes) provides better ability (like for like) to detect a difference between the groups.
Plain Language Summary
Simple linear regression can be used to analyze DAH30 outcome in a randomized trial for a range of scenarios which were considered in this study (including relatively proportions of zero values). The DAH30's properties affect the treatment effect than can be estimated. Mann-Whitney test offered better ability to detect a difference of a smaller magnitude for smaller samples sizes.
期刊介绍:
The Journal of Clinical Epidemiology strives to enhance the quality of clinical and patient-oriented healthcare research by advancing and applying innovative methods in conducting, presenting, synthesizing, disseminating, and translating research results into optimal clinical practice. Special emphasis is placed on training new generations of scientists and clinical practice leaders.