Pub Date : 2022-05-20DOI: 10.1007/s12561-022-09344-8
An-Shun Tai, Chun-Chao Wang, Wen-Ping Hsieh
{"title":"Detection of Cell Separation-Induced Gene Expression Through a Penalized Deconvolution Approach","authors":"An-Shun Tai, Chun-Chao Wang, Wen-Ping Hsieh","doi":"10.1007/s12561-022-09344-8","DOIUrl":"https://doi.org/10.1007/s12561-022-09344-8","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45317080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1007/s12561-021-09311-9
Soutik Ghosal, Zhen Chen
Predicting large fetuses at birth is of great interest to obstetricians. Using an NICHD Scandinavian Study that collected longitudinal ultrasound examination data during pregnancy, we estimate diagnostic accuracy parameters of estimated fetal weight (EFW) at various times during pregnancy in predicting large-for-gestational-age. We adopt a placement value based Bayesian regression model with random effects to estimate ROC curves. The use of placement values allows us to model covariate effects directly on the ROC curves and the adoption of a Bayesian approach accommodates the a priori constraint that an ROC curve of EFW near delivery should dominate another further away. The proposed methodology is shown to perform better than some alternative approaches in simulations and its application to the Scandinavian Study data suggests that diagnostic accuracy of EFW can improve about 65% from week 17 to 37 of gestation.
{"title":"Discriminatory capacity of prenatal ultrasound measures for large-for-gestational-age birth: A Bayesian approach to ROC analysis using placement values.","authors":"Soutik Ghosal, Zhen Chen","doi":"10.1007/s12561-021-09311-9","DOIUrl":"https://doi.org/10.1007/s12561-021-09311-9","url":null,"abstract":"<p><p>Predicting large fetuses at birth is of great interest to obstetricians. Using an NICHD Scandinavian Study that collected longitudinal ultrasound examination data during pregnancy, we estimate diagnostic accuracy parameters of estimated fetal weight (EFW) at various times during pregnancy in predicting large-for-gestational-age. We adopt a placement value based Bayesian regression model with random effects to estimate ROC curves. The use of placement values allows us to model covariate effects directly on the ROC curves and the adoption of a Bayesian approach accommodates the <i>a priori</i> constraint that an ROC curve of EFW near delivery should dominate another further away. The proposed methodology is shown to perform better than some alternative approaches in simulations and its application to the Scandinavian Study data suggests that diagnostic accuracy of EFW can improve about 65% from week 17 to 37 of gestation.</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s12561-021-09311-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9233024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-31DOI: 10.1007/s12561-022-09342-w
Lanju Zhang, Zailong Wang, Li Wang, Lu Cui, J. Sokolove, Ivan S. F. Chan
{"title":"A Simple Approach to Incorporating Historical Control Data in Clinical Trial Design and Analysis","authors":"Lanju Zhang, Zailong Wang, Li Wang, Lu Cui, J. Sokolove, Ivan S. F. Chan","doi":"10.1007/s12561-022-09342-w","DOIUrl":"https://doi.org/10.1007/s12561-022-09342-w","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43178218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-03-04DOI: 10.1007/s12561-022-09339-5
Ruiwen Zhou, Jianguo Sun
{"title":"Estimation of the Proportional Mean Residual Life Model with Internal and Longitudinal Covariates","authors":"Ruiwen Zhou, Jianguo Sun","doi":"10.1007/s12561-022-09339-5","DOIUrl":"https://doi.org/10.1007/s12561-022-09339-5","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43677213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-16DOI: 10.1007/s12561-022-09334-w
Mingyang Shan, D. Faries, A. Dang, Xiang Zhang, Z. Cui, K. Sheffield
{"title":"A Simulation-Based Evaluation of Statistical Methods for Hybrid Real-World Control Arms in Clinical Trials","authors":"Mingyang Shan, D. Faries, A. Dang, Xiang Zhang, Z. Cui, K. Sheffield","doi":"10.1007/s12561-022-09334-w","DOIUrl":"https://doi.org/10.1007/s12561-022-09334-w","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48937504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-02-08DOI: 10.1007/s12561-022-09337-7
A. Majumdar, Ruthanna C Davi, M. Bexon, C. Chandhasin, M. Coello, F. Merchant, N. Merchant
{"title":"Building an External Control Arm for Development of a New Molecular Entity: An Application in a Recurrent Glioblastoma Trial for MDNA55","authors":"A. Majumdar, Ruthanna C Davi, M. Bexon, C. Chandhasin, M. Coello, F. Merchant, N. Merchant","doi":"10.1007/s12561-022-09337-7","DOIUrl":"https://doi.org/10.1007/s12561-022-09337-7","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46910445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-31DOI: 10.1007/s12561-022-09335-9
Jingsi Ming, Jia Zhao, Can-Hua Yang
{"title":"scPI: A Scalable Framework for Probabilistic Inference in Single-Cell RNA-Sequencing Data Analysis","authors":"Jingsi Ming, Jia Zhao, Can-Hua Yang","doi":"10.1007/s12561-022-09335-9","DOIUrl":"https://doi.org/10.1007/s12561-022-09335-9","url":null,"abstract":"","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42161841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01Epub Date: 2021-09-21DOI: 10.1007/s12561-021-09322-6
Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He
[This corrects the article DOI: 10.1007/s12561-021-09320-8.].
[这更正了文章DOI: 10.1007/s12561-021-09320-8]。
{"title":"Correction to: Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times.","authors":"Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He","doi":"10.1007/s12561-021-09322-6","DOIUrl":"https://doi.org/10.1007/s12561-021-09322-6","url":null,"abstract":"<p><p>[This corrects the article DOI: 10.1007/s12561-021-09320-8.].</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453254/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39452012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01Epub Date: 2021-09-09DOI: 10.1007/s12561-021-09320-8
Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He
To confine the spread of an infectious disease, setting a sensible quarantine time is crucial. To this end, it is imperative to well understand the distribution of incubation times of the disease. Regarding the ongoing COVID-19 pandemic, 14-days is commonly taken as a quarantine time to curb the virus spread in balancing the impacts of COVID-19 on diverse aspects of the society, including public health, economy, and humanity perspectives, etc. However, setting a sensible quarantine time is not trivial and it depends on various underlying factors. In this article, we take an angle of examining the distribution of the COVID-19 incubation time using likelihood-based methods. Our study is carried out on a dataset of 178 COVID-19 cases dated from January 20, 2020 to February 29, 2020, with the information of exposure periods and dates of symptom onset collected. To gain a good understanding of possible scenarios, we employ different models to describe incubation times of COVID-19. Our findings suggest that statistically, the 14-day quarantine time may not be long enough to control the probability of an early release of infected individuals to be small. While the size of the study data is not large enough to offer us a definitely acceptable quarantine time, and further in practice, the decision-makers may take account of other factors related to social and economic concerns to set up a practically acceptable quarantine time, our study demonstrates useful methods to determine a reasonable quarantine time from a statistical standpoint. Further, it reveals some associated complexity for fully understanding the COVID-19 incubation time distribution.
Supplementary information: The online version contains supplementary material available at 10.1007/s12561-021-09320-8.
{"title":"Is 14-Days a Sensible Quarantine Length for COVID-19? Examinations of Some Associated Issues with a Case Study of COVID-19 Incubation Times.","authors":"Yasin Khadem Charvadeh, Grace Y Yi, Yuan Bian, Wenqing He","doi":"10.1007/s12561-021-09320-8","DOIUrl":"https://doi.org/10.1007/s12561-021-09320-8","url":null,"abstract":"<p><p>To confine the spread of an infectious disease, setting a sensible quarantine time is crucial. To this end, it is imperative to well understand the distribution of incubation times of the disease. Regarding the ongoing COVID-19 pandemic, 14-days is commonly taken as a quarantine time to curb the virus spread in balancing the impacts of COVID-19 on diverse aspects of the society, including public health, economy, and humanity perspectives, etc. However, setting a sensible quarantine time is not trivial and it depends on various underlying factors. In this article, we take an angle of examining the distribution of the COVID-19 incubation time using likelihood-based methods. Our study is carried out on a dataset of 178 COVID-19 cases dated from January 20, 2020 to February 29, 2020, with the information of exposure periods and dates of symptom onset collected. To gain a good understanding of possible scenarios, we employ different models to describe incubation times of COVID-19. Our findings suggest that statistically, the 14-day quarantine time may not be long enough to control the probability of an early release of infected individuals to be small. While the size of the study data is not large enough to offer us a definitely acceptable quarantine time, and further in practice, the decision-makers may take account of other factors related to social and economic concerns to set up a practically acceptable quarantine time, our study demonstrates useful methods to determine a reasonable quarantine time from a statistical standpoint. Further, it reveals some associated complexity for fully understanding the COVID-19 incubation time distribution.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s12561-021-09320-8.</p>","PeriodicalId":45094,"journal":{"name":"Statistics in Biosciences","volume":null,"pages":null},"PeriodicalIF":1.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8428508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39416422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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