Japanese journal of biometrics最新文献_第6页

A Stepwise Variable Selection for a Cox Proportional Hazards Cure Model with Application to Breast Cancer Data Cox比例风险治愈模型的逐步变量选择及其在乳腺癌数据中的应用

Japanese journal of biometrics Pub Date : 2013-08-31 DOI: 10.5691/JJB.34.21

J. Asano, A. Hirakawa, C. Hamada

{"title":"A Stepwise Variable Selection for a Cox Proportional Hazards Cure Model with Application to Breast Cancer Data","authors":"J. Asano, A. Hirakawa, C. Hamada","doi":"10.5691/JJB.34.21","DOIUrl":"https://doi.org/10.5691/JJB.34.21","url":null,"abstract":"A cure rate model is a survival model incorporating the cure rate on the assumption that a population contains both uncured and cured individuals. It is a powerful statistical tool for cancer prognostic studies. In order to accurately predict longterm outcome the proportional hazards (PH) cure model requires variable selection methods. However, no specific variable selection method for the PH cure model has been established in practice. In this study, we present a stepwise variable selection method for the PH cure model with a logistic regression for the cure rate and a Cox regression for the hazard for uncured patients. We conducted simulation studies to evaluate the operating characteristics of the stepwise method in comparison to those of the best subset selection method based on Akaike information criterion and of the convenience variable selection method that puts all variables in the PH cure model and selects the significant ones. The results demonstrated that in many cases the stepwise method outperformed other methods with respect to false positive determinations and estimation bias for the survival curve. In addition, we demonstrated the usefulness of the stepwise method for the PH cure model by applying it to analyze clinical data on breast cancer patients.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132501250","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}

引用次数: 6

脳 MRI データの統計解析脑部MRI数据的统计分析

Japanese journal of biometrics Pub Date : 2013-02-28 DOI: 10.5691/JJB.33.145

淳川口

引用次数: 0

Multiple Imputation 法によるネステッドケースコントロール研究，ケースコホート研究の解析基于Multiple Imputation法的netted情况控制研究，情况类别研究的解析

Japanese journal of biometrics Pub Date : 2013-02-28 DOI: 10.5691/JJB.33.101

久史野間, 司朗田中, 田中佐智子, 和泉志津恵

引用次数: 2

連続再評価法とその周辺（II）—連続再評価法の修正・拡張版と関連デザイン— 连续重估法及其周边(II)—连续重估法的修改和扩展版及相关设计—

Japanese journal of biometrics Pub Date : 2012-08-31 DOI: 10.5691/JJB.33.31

貴志大門

引用次数: 0

連続再評価法とその周辺（I）—連続再評価法とは— 连续重估法及其周围(I)——连续重估法是指——

Japanese journal of biometrics Pub Date : 2012-08-31 DOI: 10.5691/JJB.33.1

貴志大門

引用次数: 0

Application of a Change Point Model to Atomic-Bomb Survivor Data: Radiation Risk of Noncancer Disease Mortality 变化点模型在原子弹幸存者数据中的应用:非癌症疾病死亡率的辐射风险

Japanese journal of biometrics Pub Date : 2012-03-31 DOI: 10.5691/JJB.32.75

Yoshisuke Nonaka, Y. Shimizu, K. Ozasa, Munechika Misumi, H. Cullings, F. Kasagi

{"title":"Application of a Change Point Model to Atomic-Bomb Survivor Data: Radiation Risk of Noncancer Disease Mortality","authors":"Yoshisuke Nonaka, Y. Shimizu, K. Ozasa, Munechika Misumi, H. Cullings, F. Kasagi","doi":"10.5691/JJB.32.75","DOIUrl":"https://doi.org/10.5691/JJB.32.75","url":null,"abstract":"要約放射線影響研究所が追跡調査している原爆被爆者集団(寿命調査集団)におけるがん以外の疾患による死亡の線量反応の形状は期間により異なっている。本研究では、変化点モデルと赤池情報量規準(AIC)を、公開されている寿命調査報告書第 13報(Preston et al.、2003年)のデータに適用した。このデータには、対象者86,572人とその1950–1997年の追跡調査期間中のがん以外の疾患死亡者 31,881 人が含まれている。線量反応には変化点モデルを用いたがバックグラウンドには変化点モデルを用いなかった解析では、寿命調査報告書第 13 報と同様の結果が示された。つまり、近距離被爆者と遠距離被爆者のがん以外の疾患による基準死亡率の差が時間によって変化し、線量反応の形状は 1950–1967 年では線形二次、1968–1997 年では線形であった。しかし、線量反応だけでなくバックグラウンドにも変化点モデルを用いた今回のモデルでは、近距離被爆者と遠距離被爆者のがん以外の疾患による基準死亡率の差が時間によって変化することを示す証拠はほとんど得られなかった。線量反応の形状は、1950–1964 年では純粋な二次、1965–1997 年では線形であった。また、がん以外の疾患による死亡を循環器疾患とその他のがん以外の疾患に分けた場合、線量反応の形状は期間によって変わらなかった。(循環器疾患の線量反応は線形、その他のがん以外の疾患の線量反応は純粋な二次であった)。","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131879591","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}

引用次数: 2

日本における MBDD の現状の問題点と今後の課題日本MBDD现状的问题和今后的课题

Japanese journal of biometrics Pub Date : 2011-12-31 DOI: 10.5691/JJB.32.S195

英史笠井

引用次数: 0

Model-Based Drug Developmentの事例模型- based Drug Development的案例

Japanese journal of biometrics Pub Date : 2011-12-31 DOI: 10.5691/JJB.32.179

完爾小松

引用次数: 0

Modifications of QIC and CIC for Selecting a Working Correlation Structure in the Generalized Estimating Equation Method 广义估计方程法中选择工作相关结构的QIC和CIC的改进

Japanese journal of biometrics Pub Date : 2011-07-31 DOI: 10.5691/JJB.32.1

M. Gosho, C. Hamada, I. Yoshimura

引用次数: 5

Improvement of Statistical Power to Detect Publication Bias in Meta-analysis Using the Clinical Trial Registration System 利用临床试验注册系统改进meta分析中检测发表偏倚的统计能力

Japanese journal of biometrics Pub Date : 2011-07-31 DOI: 10.5691/JJB.32.13

N. Matsuoka, H. Horio, C. Hamada

{"title":"Improvement of Statistical Power to Detect Publication Bias in Meta-analysis Using the Clinical Trial Registration System","authors":"N. Matsuoka, H. Horio, C. Hamada","doi":"10.5691/JJB.32.13","DOIUrl":"https://doi.org/10.5691/JJB.32.13","url":null,"abstract":"As clinical trials with “positive” results are more likely to be published, a meta-analysis of only published trials may be biased toward positive results (referred to as “publication bias”). A number of statistical tests have been proposed to detect publication bias. However, they have undesirable properties, particularly, the inflation of type I error and low power. A primordial countermeasure has been launched. In September 2004, the International Committee of Medical Journal Editors announced that they would no longer publish trials that were not registered in a public registry in advance. They embraced the WHO trial registration set consisting of 20 items including target sample size, which is related to the publication of results. The aim of this paper is to propose a new approach with a higher statistical power for detecting publication bias by using information on the sample sizes of all trials, including unpublished trials from the registry. We compared the proposed method to commonly used methods via simulations. The proposed method was found to have a higher power than the other methods in many situations. It will be useful for detecting publication bias because clinical trial registration will be more widespread in the near future.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134172036","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}

引用次数: 1