The red swamp crayfish,Procambarus clarkii,is an economically important species especially in China.Their exoskeleton places serious constraints on growth and culture management.Their growth is achieved through interm...The red swamp crayfish,Procambarus clarkii,is an economically important species especially in China.Their exoskeleton places serious constraints on growth and culture management.Their growth is achieved through intermittent molting/ecdysis.The longitudinal genetic dynamics for growth-related traits at different ecdysial points in P.clarkii has been unclear to date.In this study,conditional genetic analysis was carried out for growth-related traits(body weight,body length,chela length,and cephalothorax length)based upon a mixed genetic model with conditional additive,dominance,and genotype by environment effects in P.clarkii.A complete diallel cross was made among three geographic populations of P.clarkii for the genetic mating design.Results of the conditional genetic analysis showed that from 4 th molt to 9 th molt the conditional additive variations were increased significantly whereas the conditional non-additive genetic variations(dominance and genotype by environment interaction)were decreased significantly for these growth-related traits.This indicated that lots of new expression of additive effect genes for body weight,body length,chela length,and cephalothorax length occurred during ontogeny,and environment played a signifi cant role in the expression of genes affecting these growth-related traits.Growth of the four traits was mainly affected by non-additive genetic effects in early developmental stage(prior to 4 th molt).The cumulative conditional additive variation for the growth-related traits from 4 th molt to 9 th molt accounted for a large majority of the total conditional additive variations from 2 nd molt to 9 th molt,indicating that this period was very important for the growth of this species.Using the conditional analysis method,dynamics of growth-related traits during an important ontogenetic phase of red swamp crayfish was uncovered.Our results provide valuable insights into refining production of this species.展开更多
The longitudinal structure function with shadowing correction according to the nonlinear effects of the gluon density behavior at low x is considered. The solution of the GLR-MQ evolution equation for the gluon densit...The longitudinal structure function with shadowing correction according to the nonlinear effects of the gluon density behavior at low x is considered. The solution of the GLR-MQ evolution equation for the gluon density shows that the FL^g（x, Q2） behavior can be tamed by the singularity at low x values. Comparing our results with H1 data at R=4 GeV-1 shows that at very low x this behavior is completely tamed by taking shadowing correction into account.展开更多
In the research of scientific field, it is often necessary to continuously observe different indicators of individuals at different times and analyze the observed results. Among them, variables are mainly of two types...In the research of scientific field, it is often necessary to continuously observe different indicators of individuals at different times and analyze the observed results. Among them, variables are mainly of two types: ordered variables and continuous variables. When analyzing data for different types of variables, it is necessary to consider the correlation between multiple indicators of an individual, and often perform joint analysis on variable observation data of multiple indicators of an individual at different times, in order to achieve more accurate and true analysis results. Joint analysis often yields more information than separate analysis of various variables. In this paper, the ordered variable and the continuous variable are numerically modeled. Based on the potential variable model, the multivariate longitudinal data containing the ordered variable and the continuous variable are jointly analyzed, and the approximate value of the edge likelihood can be obtained by using the method of numerical integration.展开更多
Osteoporosis is a known risk factor for rotator cuff tears(RCTs),but the causal correlation and underlying mechanisms remain unclear.This study aims to evaluate the impact of osteoporosis on RCT risk and investigate t...Osteoporosis is a known risk factor for rotator cuff tears(RCTs),but the causal correlation and underlying mechanisms remain unclear.This study aims to evaluate the impact of osteoporosis on RCT risk and investigate their genetic associations.Using data from the UK Biobank(n=457871),cross-sectional analyses demonstrated that osteoporosis was significantly associated with an increased risk of RCTs(adjusted OR[95%CI]=1.38[1.25–1.52]).A longitudinal analysis of a subset of patients(n=268117)over 11 years revealed that osteoporosis increased the risk of RCTs(adjusted HR[95%CI]=1.56[1.29–1.87]),which is notably varied between sexes in sex-stratified analysis.Causal inference methods,including propensity score matching,inverse probability weighting,causal random forest and survival random forest models further confirmed the causal effect,both from cross-sectional and longitudinal perspectives.展开更多
Objective:This study aimed to examine the developmental trajectories of internalizing behaviors among adolescents and to identify key personal and environmental factors associated with these developmental patterns ove...Objective:This study aimed to examine the developmental trajectories of internalizing behaviors among adolescents and to identify key personal and environmental factors associated with these developmental patterns over time.Methods:Data were collected from 2242 adolescents(49.6%girls,aged 13.9–18.9 years)in South Korea.Latent class growth analysis was used to identify distinct developmental patterns of internalizing behaviors.Multinomial logistic regression analyses were conducted to examine the associations between these developmental patterns and various factors including gender,self-esteem,abuse and neglect experiences,peer relationships,and media use.Results:The analysis revealed three latent classes of internalizing behavior trajectories among adolescents.The first group,the“mid decreasing group”,comprised 54.5%of the sample(1221 students),indicating a moderate level of internalizing behavior that declined over time.The second group,the“high decreasing group”,included 19.1%of the sample(429 students),characterized by initially high levels of internalizing behavior that decreased.The third group,the“low maintained group”,represented 26.4%of the sample(592 students),indicating consistently low levels of internalizing behavior.Factors such as gender,self-esteem,experiences of abuse and neglect,peer relationships(trust and alienation),smartphone dependency,and time spent watching TV/videos were significantly associated with these latent groups.Conclusion:Three distinct developmental patterns of internalizing behaviors were identified among adolescents:mid-decreasing(54.5%),high-decreasing(19.1%),and low-maintained(26.4%).Gender,self-esteem,abuse experiences,and peer relationships were significant predictors of these developmental patterns.展开更多
This letter critically reviews a recent longitudinal network study by Bai et al examining the dynamic,symptom-level interplay among peer bullying victimization,depression,anxiety,and aggression in Chinese adolescents....This letter critically reviews a recent longitudinal network study by Bai et al examining the dynamic,symptom-level interplay among peer bullying victimization,depression,anxiety,and aggression in Chinese adolescents.The study highlights that key symptoms,such as persistent sad mood,sleep disturbances,and cyberbullying victimization play a pivotal role in reinforcing the vicious cycle between mental health issues and bullying experiences.While the application of cross-lagged panel network analysis offers a nuanced understanding of these bidirectional relationships,several limitations remain,including the use of selfreported measures and a region-specific sample.Nevertheless,the findings underscore the urgent need for early screening and targeted interventions in school settings,particularly those addressing both emotional symptoms and digital forms of bullying.Moving forward,integrated and culturally sensitive approaches are essential to prevent escalation and break the link between peer victimization and adolescent psychopathology.Future research should incorporate multi-informant data and broaden the cultural context to strengthen generalizability and intervention design.展开更多
In disaster response,collaboration facilitates interactions among actors,such as the government,the military,nongovernmental organizations,and civil society organizations.This study examined the longitudinal changes i...In disaster response,collaboration facilitates interactions among actors,such as the government,the military,nongovernmental organizations,and civil society organizations.This study examined the longitudinal changes in collaborative governance in Myanmar’s disaster responses based on cases of flooding in 2015,2016,and 2018.To examine the mechanisms underlying this dynamic network formation,the collaborative ties of the actors involved in search and rescue activities were converted into longitudinal relational data sets,and the evolution of collaborative governance was analyzed by relying on the assumptions of social capital,transaction cost,homophily,and resource dependency theories and using a longitudinal social network analysis method.The findings show that the collaborative networks of search and rescue processes in disaster response evolved and changed over time according to the hypothesized patterns of strong,weak,and preferential tie formations.The study also revealed that the collaborative governance system assumes the form of a hierarchy rather than a generalized exchange,and the actors’reliance on military organizations is not obvious due to the emerging alternative non-military actors and diverse local actors observed in the cases.展开更多
Longitudinal image analysis plays an important role in depicting the development of the brain structure,where image regression and interpolation are two commonly used techniques.In this paper,we develop an efficient m...Longitudinal image analysis plays an important role in depicting the development of the brain structure,where image regression and interpolation are two commonly used techniques.In this paper,we develop an efficient model and approach based on a path regression on the image manifold instead of the geodesic regression to avoid the complexity of the geodesic computation.Concretely,first we model the deformation by diffeomorphism;then,a large deformation is represented by a path on the orbit of the diffeomorphism group action.This path is obtained by compositing several small deformations,which can be well approximated by its linearization.Second,we introduce some intermediate images as constraints to the model,which guides to form the best-fitting path.Thirdly,we propose an approximated quadratic model by local linearization method,where a closed form is deduced for the solution.It actually speeds up the algorithm.Finally,we evaluate the proposed model and algorithm on a synthetic data and a real longitudinal MRI data.The results show that our proposed method outperforms several state-of-the-art methods.展开更多
In genetic studies of complex diseases, particularly mental illnesses, and behavior disorders, two distinct characteristics have emerged in some data sets. First, genetic data sets are collected with a large number of...In genetic studies of complex diseases, particularly mental illnesses, and behavior disorders, two distinct characteristics have emerged in some data sets. First, genetic data sets are collected with a large number of phenotypes that are potentially related to the complex disease under study. Second, each phenotype is collected from the same subject repeatedly over time. In this study, we present a nonparametric regression approach to study multivariate and time-repeated phenotypes together by using the technique of the multivariate adaptive regression splines for analysis of longitudinal data （MASAL）, which makes it possible to identify genes, gene-gene and gene-environment, including time, interactions associated with the phenotypes of interest. Furthermore, we propose a permutation test to assess the associations between the phenotypes and selected markers. Through simulation, we demonstrate that our proposed approach has advantages over the existing methods that examine each longitudinal phenotype separately or analyze the summarized values of phenotypes by compressing them into one-time-point phenotypes. Application of the proposed method to the Framingham Heart Study illustrates that the use of multivariate longitudinal phenotypes enhanced the significance of the association test.展开更多
Long-term exposure to fine particulate matter(PM_(2.5))has been linked with adverse mental health outcomes.However,questions remain regarding the nature of lagged effects over time and by extension potential benefits ...Long-term exposure to fine particulate matter(PM_(2.5))has been linked with adverse mental health outcomes.However,questions remain regarding the nature of lagged effects over time and by extension potential benefits over time of continued reduction in pollution.Here,we aim to estimate the long-term association between exposure to PM_(2.5)and depressive symptoms in China utilizing longitudinal models for prolonged exposures as well as a quasi-experimental design utilizing data from 23151 participants over 4 longitudinal waves that occurred in 124 cities in China between 2011 to 2018.Mixed-effects models as well as distributed lag nonlinear mixed models were fitted to assess the relationship between PM_(2.5)and depressive symptoms.We also assessed the effect of the Clean Air Policy(CAP)based on a quasi-experimental difference-in-differences(DID)design.The overall average PM_(2.5)concentrations generally declined with time from 59.40 to 39.35μg/m^(3).A 10μg/m^(3)increase in PM_(2.5)concentration was associated with a 0.86%increase(95%confidence interval[CI]:0.1,1.64%)in depression score based on the first three waves of data.However,the associations were sensitive to secular trends.Flexible exposure-lag-response analysis indicated a potentially influential window for lag-years 0-6.Reduction in PM_(2.5)led to 19.51%([CI]:11.57%,26.73%)and 28.18%,([CI]:5.87%,45.2%)lower depressive scores in waves 3 and 4,respectively,compared to no reduction or increase in exposures.Our analysis suggests an association between PM_(2.5)and depressive symptoms with potential long-term effects of air pollution as well as potential for continued benefit of air pollution reduction over time.展开更多
Ovarian cancer is one of the most deadly female genital malignant tumors in many regions while an effective early screening strategy can save numerous lives.CA125 and HE4 are tumor markers validated efficacious as wel...Ovarian cancer is one of the most deadly female genital malignant tumors in many regions while an effective early screening strategy can save numerous lives.CA125 and HE4 are tumor markers validated efficacious as well as most commonly used in recent screening research of ovarian cancer.In this paper,the authors construct a change-point and mixture model on the basis of longitudinal CA125 and HE4 levels and estimated parameters using maximum likelihood method with the preclinical duration assumed right-censored,which is more adaptive and yields comparable results in comparison to the Bayesian approach raised by Skates.Consistency of estimators is proved.The authors also run a 5-year simulation of sequential screening by calculating the risk of cancer and hypothesis testing the true incidence time respectively.Results show that diagnosis based on hypothesis test performs better in early detection.展开更多
基金Supported by the National Natural Science Foundation of China(No.31672648)the Jiangsu Collaborative Innovation Center of Regional Modern Agriculture&Environmental Protection and Huaiyin Normal University(No.HSXT2-107)the Science&Technology Program of Huaiyin Normal University(No.31WH000)。
文摘The red swamp crayfish,Procambarus clarkii,is an economically important species especially in China.Their exoskeleton places serious constraints on growth and culture management.Their growth is achieved through intermittent molting/ecdysis.The longitudinal genetic dynamics for growth-related traits at different ecdysial points in P.clarkii has been unclear to date.In this study,conditional genetic analysis was carried out for growth-related traits(body weight,body length,chela length,and cephalothorax length)based upon a mixed genetic model with conditional additive,dominance,and genotype by environment effects in P.clarkii.A complete diallel cross was made among three geographic populations of P.clarkii for the genetic mating design.Results of the conditional genetic analysis showed that from 4 th molt to 9 th molt the conditional additive variations were increased significantly whereas the conditional non-additive genetic variations(dominance and genotype by environment interaction)were decreased significantly for these growth-related traits.This indicated that lots of new expression of additive effect genes for body weight,body length,chela length,and cephalothorax length occurred during ontogeny,and environment played a signifi cant role in the expression of genes affecting these growth-related traits.Growth of the four traits was mainly affected by non-additive genetic effects in early developmental stage(prior to 4 th molt).The cumulative conditional additive variation for the growth-related traits from 4 th molt to 9 th molt accounted for a large majority of the total conditional additive variations from 2 nd molt to 9 th molt,indicating that this period was very important for the growth of this species.Using the conditional analysis method,dynamics of growth-related traits during an important ontogenetic phase of red swamp crayfish was uncovered.Our results provide valuable insights into refining production of this species.
文摘The longitudinal structure function with shadowing correction according to the nonlinear effects of the gluon density behavior at low x is considered. The solution of the GLR-MQ evolution equation for the gluon density shows that the FL^g（x, Q2） behavior can be tamed by the singularity at low x values. Comparing our results with H1 data at R=4 GeV-1 shows that at very low x this behavior is completely tamed by taking shadowing correction into account.
文摘In the research of scientific field, it is often necessary to continuously observe different indicators of individuals at different times and analyze the observed results. Among them, variables are mainly of two types: ordered variables and continuous variables. When analyzing data for different types of variables, it is necessary to consider the correlation between multiple indicators of an individual, and often perform joint analysis on variable observation data of multiple indicators of an individual at different times, in order to achieve more accurate and true analysis results. Joint analysis often yields more information than separate analysis of various variables. In this paper, the ordered variable and the continuous variable are numerically modeled. Based on the potential variable model, the multivariate longitudinal data containing the ordered variable and the continuous variable are jointly analyzed, and the approximate value of the edge likelihood can be obtained by using the method of numerical integration.
文摘Microscopic imaging based on second-harmonic generation has been proving to be a powerful tool for biomedical studies, especially in that tissues with
基金the Scientific Research Innovation Capability Support Project for Young Faculty(ZYGXQNJSKYCXNLZCXM-H8)Fundamental Research Funds for the Central Universities(2024ZYGXZR077)+3 种基金Guangdong Basic and Applied Basic Research Foundation(2023B1515120006)Guangzhou Basic and Applied Basic Research Foundation(2024A04J5776)the Research Fund(2023QN10Y421)Guangzhou Talent Recruitment Team Program(2024D03J0004),all related to this study.
文摘Osteoporosis is a known risk factor for rotator cuff tears(RCTs),but the causal correlation and underlying mechanisms remain unclear.This study aims to evaluate the impact of osteoporosis on RCT risk and investigate their genetic associations.Using data from the UK Biobank(n=457871),cross-sectional analyses demonstrated that osteoporosis was significantly associated with an increased risk of RCTs(adjusted OR[95%CI]=1.38[1.25–1.52]).A longitudinal analysis of a subset of patients(n=268117)over 11 years revealed that osteoporosis increased the risk of RCTs(adjusted HR[95%CI]=1.56[1.29–1.87]),which is notably varied between sexes in sex-stratified analysis.Causal inference methods,including propensity score matching,inverse probability weighting,causal random forest and survival random forest models further confirmed the causal effect,both from cross-sectional and longitudinal perspectives.
文摘Objective:This study aimed to examine the developmental trajectories of internalizing behaviors among adolescents and to identify key personal and environmental factors associated with these developmental patterns over time.Methods:Data were collected from 2242 adolescents(49.6%girls,aged 13.9–18.9 years)in South Korea.Latent class growth analysis was used to identify distinct developmental patterns of internalizing behaviors.Multinomial logistic regression analyses were conducted to examine the associations between these developmental patterns and various factors including gender,self-esteem,abuse and neglect experiences,peer relationships,and media use.Results:The analysis revealed three latent classes of internalizing behavior trajectories among adolescents.The first group,the“mid decreasing group”,comprised 54.5%of the sample(1221 students),indicating a moderate level of internalizing behavior that declined over time.The second group,the“high decreasing group”,included 19.1%of the sample(429 students),characterized by initially high levels of internalizing behavior that decreased.The third group,the“low maintained group”,represented 26.4%of the sample(592 students),indicating consistently low levels of internalizing behavior.Factors such as gender,self-esteem,experiences of abuse and neglect,peer relationships(trust and alienation),smartphone dependency,and time spent watching TV/videos were significantly associated with these latent groups.Conclusion:Three distinct developmental patterns of internalizing behaviors were identified among adolescents:mid-decreasing(54.5%),high-decreasing(19.1%),and low-maintained(26.4%).Gender,self-esteem,abuse experiences,and peer relationships were significant predictors of these developmental patterns.
基金Supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,No.NRF-RS-2023-00237287。
文摘This letter critically reviews a recent longitudinal network study by Bai et al examining the dynamic,symptom-level interplay among peer bullying victimization,depression,anxiety,and aggression in Chinese adolescents.The study highlights that key symptoms,such as persistent sad mood,sleep disturbances,and cyberbullying victimization play a pivotal role in reinforcing the vicious cycle between mental health issues and bullying experiences.While the application of cross-lagged panel network analysis offers a nuanced understanding of these bidirectional relationships,several limitations remain,including the use of selfreported measures and a region-specific sample.Nevertheless,the findings underscore the urgent need for early screening and targeted interventions in school settings,particularly those addressing both emotional symptoms and digital forms of bullying.Moving forward,integrated and culturally sensitive approaches are essential to prevent escalation and break the link between peer victimization and adolescent psychopathology.Future research should incorporate multi-informant data and broaden the cultural context to strengthen generalizability and intervention design.
文摘In disaster response,collaboration facilitates interactions among actors,such as the government,the military,nongovernmental organizations,and civil society organizations.This study examined the longitudinal changes in collaborative governance in Myanmar’s disaster responses based on cases of flooding in 2015,2016,and 2018.To examine the mechanisms underlying this dynamic network formation,the collaborative ties of the actors involved in search and rescue activities were converted into longitudinal relational data sets,and the evolution of collaborative governance was analyzed by relying on the assumptions of social capital,transaction cost,homophily,and resource dependency theories and using a longitudinal social network analysis method.The findings show that the collaborative networks of search and rescue processes in disaster response evolved and changed over time according to the hypothesized patterns of strong,weak,and preferential tie formations.The study also revealed that the collaborative governance system assumes the form of a hierarchy rather than a generalized exchange,and the actors’reliance on military organizations is not obvious due to the emerging alternative non-military actors and diverse local actors observed in the cases.
基金The research was supported by the National Natural Science Foundation of China(Nos.11771276,11471208)the Capacity Construction Project of Local Universities in Shanghai(No.18010500600).
文摘Longitudinal image analysis plays an important role in depicting the development of the brain structure,where image regression and interpolation are two commonly used techniques.In this paper,we develop an efficient model and approach based on a path regression on the image manifold instead of the geodesic regression to avoid the complexity of the geodesic computation.Concretely,first we model the deformation by diffeomorphism;then,a large deformation is represented by a path on the orbit of the diffeomorphism group action.This path is obtained by compositing several small deformations,which can be well approximated by its linearization.Second,we introduce some intermediate images as constraints to the model,which guides to form the best-fitting path.Thirdly,we propose an approximated quadratic model by local linearization method,where a closed form is deduced for the solution.It actually speeds up the algorithm.Finally,we evaluate the proposed model and algorithm on a synthetic data and a real longitudinal MRI data.The results show that our proposed method outperforms several state-of-the-art methods.
基金The authors thank two anonymous referees for their constructive comments and suggestions. This work was supported by grant R01 DA016750-09 from the National Institute on Drug Abuse. Zhu＇s work was also supported by the National Natural Science Foundation of China （Grant No. 11001044）, the Yhndamental Research ~nds for the Central Universities （11CXPY007, 10JCXK001）, the Natural Science Foundation of Jilin Province （Grant No. 201215007）, the Scientific Research Foundation for Returned Scholars, MOE of China, and the Program for Changjiang Scholars and Innovative Research Team in University. The Framingham Heart Study project is conducted and supported by the National Heart, Lung, and Blood Institute （NHLBI） in collaboration with Boston University （N01 HC25195）. The Framingham data used for the analyses described in this manuscript were obtained through dbGaP （phs000128.v3.p3）.
文摘In genetic studies of complex diseases, particularly mental illnesses, and behavior disorders, two distinct characteristics have emerged in some data sets. First, genetic data sets are collected with a large number of phenotypes that are potentially related to the complex disease under study. Second, each phenotype is collected from the same subject repeatedly over time. In this study, we present a nonparametric regression approach to study multivariate and time-repeated phenotypes together by using the technique of the multivariate adaptive regression splines for analysis of longitudinal data （MASAL）, which makes it possible to identify genes, gene-gene and gene-environment, including time, interactions associated with the phenotypes of interest. Furthermore, we propose a permutation test to assess the associations between the phenotypes and selected markers. Through simulation, we demonstrate that our proposed approach has advantages over the existing methods that examine each longitudinal phenotype separately or analyze the summarized values of phenotypes by compressing them into one-time-point phenotypes. Application of the proposed method to the Framingham Heart Study illustrates that the use of multivariate longitudinal phenotypes enhanced the significance of the association test.
基金supported by the National Natural Science Foundation of China(Grant No.42225104)National Institute of Environmental Health Sciences(NIEHS)of the United States(Grant No.R00ES027511)+2 种基金National Natural Science Foundation of China(Grant No.42201303)National Natural Science Foundation of China(Grant No.U21A2010)Thanks to support from the Foundamental Research Youth Team Project of the Chinese Academy of Science.
文摘Long-term exposure to fine particulate matter(PM_(2.5))has been linked with adverse mental health outcomes.However,questions remain regarding the nature of lagged effects over time and by extension potential benefits over time of continued reduction in pollution.Here,we aim to estimate the long-term association between exposure to PM_(2.5)and depressive symptoms in China utilizing longitudinal models for prolonged exposures as well as a quasi-experimental design utilizing data from 23151 participants over 4 longitudinal waves that occurred in 124 cities in China between 2011 to 2018.Mixed-effects models as well as distributed lag nonlinear mixed models were fitted to assess the relationship between PM_(2.5)and depressive symptoms.We also assessed the effect of the Clean Air Policy(CAP)based on a quasi-experimental difference-in-differences(DID)design.The overall average PM_(2.5)concentrations generally declined with time from 59.40 to 39.35μg/m^(3).A 10μg/m^(3)increase in PM_(2.5)concentration was associated with a 0.86%increase(95%confidence interval[CI]:0.1,1.64%)in depression score based on the first three waves of data.However,the associations were sensitive to secular trends.Flexible exposure-lag-response analysis indicated a potentially influential window for lag-years 0-6.Reduction in PM_(2.5)led to 19.51%([CI]:11.57%,26.73%)and 28.18%,([CI]:5.87%,45.2%)lower depressive scores in waves 3 and 4,respectively,compared to no reduction or increase in exposures.Our analysis suggests an association between PM_(2.5)and depressive symptoms with potential long-term effects of air pollution as well as potential for continued benefit of air pollution reduction over time.
基金supported by the Ph.D. Programs Foundation of Ministry of Education of China under Grant No.20090001110005the National Natural Science Foundation of China under Grant No.11171007
文摘Ovarian cancer is one of the most deadly female genital malignant tumors in many regions while an effective early screening strategy can save numerous lives.CA125 and HE4 are tumor markers validated efficacious as well as most commonly used in recent screening research of ovarian cancer.In this paper,the authors construct a change-point and mixture model on the basis of longitudinal CA125 and HE4 levels and estimated parameters using maximum likelihood method with the preclinical duration assumed right-censored,which is more adaptive and yields comparable results in comparison to the Bayesian approach raised by Skates.Consistency of estimators is proved.The authors also run a 5-year simulation of sequential screening by calculating the risk of cancer and hypothesis testing the true incidence time respectively.Results show that diagnosis based on hypothesis test performs better in early detection.
