Scandinavian journal of statistics, theory and applications最新文献

筛选
英文 中文
Feature screening for case-cohort studies with failure time outcome. 有失败时间结局的病例队列研究的特征筛选。
IF 1
Scandinavian journal of statistics, theory and applications Pub Date : 2021-03-01 Epub Date: 2020-11-16 DOI: 10.1111/sjos.12503
Jing Zhang, Haibo Zhou, Yanyan Liu, Jianwen Cai
{"title":"Feature screening for case-cohort studies with failure time outcome.","authors":"Jing Zhang,&nbsp;Haibo Zhou,&nbsp;Yanyan Liu,&nbsp;Jianwen Cai","doi":"10.1111/sjos.12503","DOIUrl":"https://doi.org/10.1111/sjos.12503","url":null,"abstract":"<p><p>Case-cohort design has been demonstrated to be an economical and efficient approach in large cohort studies when the measurement of some covariates on all individuals is expensive. Various methods have been proposed for case-cohort data when the dimension of covariates is smaller than sample size. However, limited work has been done for high-dimensional case-cohort data which are frequently collected in large epidemiological studies. In this paper, we propose a variable screening method for ultrahigh-dimensional case-cohort data under the framework of proportional model, which allows the covariate dimension increases with sample size at exponential rate. Our procedure enjoys the sure screening property and the ranking consistency under some mild regularity conditions. We further extend this method to an iterative version to handle the scenarios where some covariates are jointly important but are marginally unrelated or weakly correlated to the response. The finite sample performance of the proposed procedure is evaluated via both simulation studies and an application to a real data from the breast cancer study.</p>","PeriodicalId":520775,"journal":{"name":"Scandinavian journal of statistics, theory and applications","volume":" ","pages":"349-370"},"PeriodicalIF":1.0,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/sjos.12503","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40590326","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}
引用次数: 3
Optimal Estimator for Logistic Model with Distribution-free Random Intercept. 无分布随机截距Logistic模型的最优估计。
IF 1
Scandinavian journal of statistics, theory and applications Pub Date : 2016-03-01 Epub Date: 2015-08-06 DOI: 10.1111/sjos.12170
Tanya P Garcia, Yanyuan Ma
{"title":"Optimal Estimator for Logistic Model with Distribution-free Random Intercept.","authors":"Tanya P Garcia,&nbsp;Yanyuan Ma","doi":"10.1111/sjos.12170","DOIUrl":"https://doi.org/10.1111/sjos.12170","url":null,"abstract":"<p><p>Logistic models with a random intercept are prevalent in medical and social research where clustered and longitudinal data are often collected. Traditionally, the random intercept in these models is assumed to follow some parametric distribution such as the normal distribution. However, such an assumption inevitably raises concerns about model misspecification and misleading inference conclusions, especially when there is dependence between the random intercept and model covariates. To protect against such issues, we use a semiparametric approach to develop a computationally simple and consistent estimator where the random intercept is distribution-free. The estimator is revealed to be optimal and achieve the efficiency bound without the need to postulate or estimate any latent variable distributions. We further characterize other general mixed models where such an optimal estimator exists.</p>","PeriodicalId":520775,"journal":{"name":"Scandinavian journal of statistics, theory and applications","volume":" ","pages":"156-171"},"PeriodicalIF":1.0,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1111/sjos.12170","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40391800","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}
引用次数: 9
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信