Masaaki Doi∗1,∗2, Kazuki Ide∗3,∗4,∗5 and Yohei Kawasaki∗3,∗5 ∗1Toray Industries, Inc. Clinical Data Science & Quality Management Department ∗2Graduate School of Science and Engineering, Chuo University ∗3Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health, Kyoto University ∗4Center for the Promotion of Interdisciplinary Education and Research, Kyoto University ∗5Department of Drug Evaluation & Informatics, School of Pharmaceutical Sciences, University of Shizuoka e-mail:Masaaki Doi@nts.toray.co.jp
{"title":"Bayesian Indexes of Superiority and Equivalence and the p-value of the F-test for the Variances of Normal Distributions","authors":"Masaaki Doi, K. Ide, Y. Kawasaki","doi":"10.5691/JJB.38.1","DOIUrl":"https://doi.org/10.5691/JJB.38.1","url":null,"abstract":"Masaaki Doi∗1,∗2, Kazuki Ide∗3,∗4,∗5 and Yohei Kawasaki∗3,∗5 ∗1Toray Industries, Inc. Clinical Data Science & Quality Management Department ∗2Graduate School of Science and Engineering, Chuo University ∗3Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health, Kyoto University ∗4Center for the Promotion of Interdisciplinary Education and Research, Kyoto University ∗5Department of Drug Evaluation & Informatics, School of Pharmaceutical Sciences, University of Shizuoka e-mail:Masaaki Doi@nts.toray.co.jp","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131940005","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}
Stepwise logistic regression is the traditional and most commonly used method for identifying biomarkers and evaluating the magnitude of their effects based on clinical data. Here, we evaluated the performance of the resampling methods leave-one-out cross-validation, 10-fold cross-validation, bootstrap, and .632+ bootstrap in terms of internal validation of prediction analysis using stepwise logistic regression. We conducted simulation studies to compare the ability of these methods to estimate prediction accuracy based on simulation settings (including statistical models) derived from two real biomarker discovery studies (Ogata et al., Leukemia Research 2012; 36: 1229–1236; Yoshimi et al., Molecular Psychiatry 2016; 21: 1504–1510). The simulation results revealed that leave-one-out cross-validation, 10-fold cross-validation, and .632+ bootstrap were comparable in terms of the root mean square error. We therefore recommend the application of these methods to similar biomarker discovery studies that involve approximately ten biomarkers with or without binary biomarkers (such as sex) and various degrees of correlation between the biomarkers. samples were defined to evaluate the methods accurately, and the cut off values were set at three values for application of ROC. Our results indicate that the performances of leave-one-out cross-validation, 10-fold cross-validation, and .632+ bootstrap are comparable under previously encountered conditions.
逐步逻辑回归是识别生物标志物并根据临床数据评估其影响程度的传统和最常用的方法。在此，我们评估了重采样方法的性能，其中留一交叉验证、10倍交叉验证、bootstrap和。632+ bootstrap在使用逐步逻辑回归的预测分析的内部验证方面。我们进行了模拟研究，以比较这些方法基于模拟设置(包括统计模型)估计预测准确性的能力，这些模拟设置来自两个真实的生物标志物发现研究(Ogata等人，Leukemia Research 2012;36: 1229 - 1236;Yoshimi et al.， Molecular Psychiatry 2016;21日:1504 - 1510)。仿真结果表明，留一交叉验证、10倍交叉验证和.632+ bootstrap在均方根误差方面具有可比性。因此，我们建议将这些方法应用于类似的生物标志物发现研究，这些研究涉及大约十种生物标志物，包括或不包括二元生物标志物(如性别)以及生物标志物之间不同程度的相关性。定义样本以准确评价方法，并将截断值设置为三个值，以便应用ROC。我们的结果表明，在先前遇到的条件下，留一交叉验证、10倍交叉验证和.632+ bootstrap的性能是相当的。
{"title":"Comparison of Resampling Methods for Bias-Reduced Estimation of Prediction Error: A Simulation Study Based on Real Datasets from Biomarker Discovery Studies","authors":"K. Kakumoto, Y. Tochizawa","doi":"10.5691/JJB.38.17","DOIUrl":"https://doi.org/10.5691/JJB.38.17","url":null,"abstract":"Stepwise logistic regression is the traditional and most commonly used method for identifying biomarkers and evaluating the magnitude of their effects based on clinical data. Here, we evaluated the performance of the resampling methods leave-one-out cross-validation, 10-fold cross-validation, bootstrap, and .632+ bootstrap in terms of internal validation of prediction analysis using stepwise logistic regression. We conducted simulation studies to compare the ability of these methods to estimate prediction accuracy based on simulation settings (including statistical models) derived from two real biomarker discovery studies (Ogata et al., Leukemia Research 2012; 36: 1229–1236; Yoshimi et al., Molecular Psychiatry 2016; 21: 1504–1510). The simulation results revealed that leave-one-out cross-validation, 10-fold cross-validation, and .632+ bootstrap were comparable in terms of the root mean square error. We therefore recommend the application of these methods to similar biomarker discovery studies that involve approximately ten biomarkers with or without binary biomarkers (such as sex) and various degrees of correlation between the biomarkers. samples were defined to evaluate the methods accurately, and the cut off values were set at three values for application of ROC. Our results indicate that the performances of leave-one-out cross-validation, 10-fold cross-validation, and .632+ bootstrap are comparable under previously encountered conditions.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114325087","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}
Multiple comparison procedures provide differences among the groups that is of interest. The procedures are used in clinical trials and agricultural fields experiments. We consider multi-sample model with Bernoulli responses under simple ordered restrictions of proportions. Shiraishi (2014b) proposed closed testing procedures based on maximum values of two-sample test statistics for all pairwise comparisons. The equality of sample sizes is needed in the asymptotic theory of Shiraishi’s procedures. We propose closed testing procedures based on statistics having asymptotically a χ̄-distribution which is appeared in Chernoff (1954). The proposed procedures are applicable for the models with unequal sample sizes. Although single-step multiple comparison procedures are utilized in general, the power of these procedures is low for a large number of groups. The closed testing procedures stated in the present paper are more powerful than the single-step procedures. Simulation studies are performed under the null hypothesis and some alternative hypotheses. In this studies, the proposed procedures show a good performance. We also illustrate applying to a dose-finding trial data with unequal sample sizes.
{"title":"Closed Testing Procedures Based on x̅ 2-Statistics in Multi-Sample Models with Bernoulli Responses under Simple Ordered Restrictions","authors":"T. Shiraishi, Shin-ichi Matsuda","doi":"10.5691/JJB.37.67","DOIUrl":"https://doi.org/10.5691/JJB.37.67","url":null,"abstract":"Multiple comparison procedures provide differences among the groups that is of interest. The procedures are used in clinical trials and agricultural fields experiments. We consider multi-sample model with Bernoulli responses under simple ordered restrictions of proportions. Shiraishi (2014b) proposed closed testing procedures based on maximum values of two-sample test statistics for all pairwise comparisons. The equality of sample sizes is needed in the asymptotic theory of Shiraishi’s procedures. We propose closed testing procedures based on statistics having asymptotically a χ̄-distribution which is appeared in Chernoff (1954). The proposed procedures are applicable for the models with unequal sample sizes. Although single-step multiple comparison procedures are utilized in general, the power of these procedures is low for a large number of groups. The closed testing procedures stated in the present paper are more powerful than the single-step procedures. Simulation studies are performed under the null hypothesis and some alternative hypotheses. In this studies, the proposed procedures show a good performance. We also illustrate applying to a dose-finding trial data with unequal sample sizes.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125804118","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}
H. Uehara, K. Satoh, Nagisa Komokata, Yohei Tokita, Mitsue Nishiyama, Maiko Iida, Junko Ishikawa, Kazuo Ogawa, Masahiro Yamamoto
In this article, we propose an alternative criterion for evaluating parallelism in parallel-line assays at the subject level. Unlike another recently proposed criterion (“ISP”; Uehara et al., 2016), this is a single criterion concerning the quantile of intrasubject slope ratio, which is straightforward to interpret. Two one-sided tolerance limits for a linear combination of the control and test slopes are developed as metrics for the evaluation of discrepancy from the ideal intrasubject parallelism. The proposed metrics are exemplified using data from two ex vivo parallel-line experiments, and their characteristics are investigated through Monte Carlo simulations.
在这篇文章中，我们提出了另一个标准，以评估平行线分析在主题水平的并行性。不像最近提出的另一个标准(“ISP”;Uehara et al.， 2016)，这是关于主体内斜率比分位数的单一标准，解释起来很简单。两个单侧公差限制的线性组合的控制和测试斜率被开发作为衡量差异的指标，从理想的主体内平行度。利用两个离体平行线实验的数据对所提出的指标进行了举例说明，并通过蒙特卡罗模拟研究了它们的特性。
{"title":"Assessment of Intrasub ject Parallelism in Ex Vivo Bioassay Using Two One-Sided Tolerance Limits","authors":"H. Uehara, K. Satoh, Nagisa Komokata, Yohei Tokita, Mitsue Nishiyama, Maiko Iida, Junko Ishikawa, Kazuo Ogawa, Masahiro Yamamoto","doi":"10.5691/JJB.37.101","DOIUrl":"https://doi.org/10.5691/JJB.37.101","url":null,"abstract":"In this article, we propose an alternative criterion for evaluating parallelism in parallel-line assays at the subject level. Unlike another recently proposed criterion (“ISP”; Uehara et al., 2016), this is a single criterion concerning the quantile of intrasubject slope ratio, which is straightforward to interpret. Two one-sided tolerance limits for a linear combination of the control and test slopes are developed as metrics for the evaluation of discrepancy from the ideal intrasubject parallelism. The proposed metrics are exemplified using data from two ex vivo parallel-line experiments, and their characteristics are investigated through Monte Carlo simulations.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127144056","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}
In clinical investigations designed to demonstrate the efficacy of a diagnostic procedure, the procedure is usually evaluated by multiple independent raters. Although the sensitivity and specificity may be estimated by considering consensus evaluations to treat results from multiple raters as if there were a single rater, raters are not consid-ered independent in consensus evaluations. Typically, estimation methods are based on an “average rater” or a “majority rater” to account for multiple raters. In this paper, we propose a method for summarizing sensitivities and specificities evaluated from multiple independent raters based on a bivariate random effects model (BVRM) to account between-rater variance and correlation between sensitivity and specificity. In addition, we propose methods to draw joint confidence regions of sensitivity and specificity based on the BVRM. Simulation results show that the differences in the biases between the proposed method and the average rater method are small and that the empirical coverage probabilities of the proposed joint confidence regions are close to the nominal level. The proposed methods are illustrated using data from florbetapir F 18 positron emission tomographic imaging to predict the presence of β -amyloid in the brains of subjects with Alzheimer’s We an If each of exceeded , the was to otherwise, it was to zero. Similarly, if each element of the matrix for the specificities exceeded z p b ) , the outcome of the element was set to one; otherwise, it was set to zero. Here, z − p ) is the 100 p percentile of the standard distribution. our simulation study, 10,000 data sets were
在旨在证明诊断程序有效性的临床调查中，该程序通常由多个独立评价者进行评估。虽然可以通过考虑共识评价来估计敏感性和特异性，将多个评分者的结果视为单一评分者，但在共识评价中，评分者并不被认为是独立的。通常，评估方法基于“平均评分者”或“多数评分者”来考虑多个评分者。在本文中，我们提出了一种基于二元随机效应模型(BVRM)的方法来总结从多个独立评分者评估的敏感性和特异性，以考虑评分者之间的方差和敏感性和特异性之间的相关性。此外，我们提出了基于brvrm的灵敏度和特异性联合置信区域的绘制方法。仿真结果表明，所提出的联合置信区域的经验覆盖概率与平均加权方法的偏差差异较小，接近于名义水平。采用florbetapir f18正电子发射断层成像的数据来说明所提出的方法，以预测阿尔茨海默病患者大脑中β -淀粉样蛋白的存在。如果每一个都超过，则为零，否则为零。同样，如果矩阵的每个元素的特异性超过z p b)，则该元素的结果设为1;否则，它被设为0。这里，z−p)是标准分布的100p个百分位数。我们的模拟研究，10000个数据集
{"title":"Estimating the Diagnostic Accuracy from Multiple Raters Based on a Bivariate Random Effects Model","authors":"H. Saeki, T. Tango, Jinfang Wang","doi":"10.5691/JJB.37.23","DOIUrl":"https://doi.org/10.5691/JJB.37.23","url":null,"abstract":"In clinical investigations designed to demonstrate the efficacy of a diagnostic procedure, the procedure is usually evaluated by multiple independent raters. Although the sensitivity and specificity may be estimated by considering consensus evaluations to treat results from multiple raters as if there were a single rater, raters are not consid-ered independent in consensus evaluations. Typically, estimation methods are based on an “average rater” or a “majority rater” to account for multiple raters. In this paper, we propose a method for summarizing sensitivities and specificities evaluated from multiple independent raters based on a bivariate random effects model (BVRM) to account between-rater variance and correlation between sensitivity and specificity. In addition, we propose methods to draw joint confidence regions of sensitivity and specificity based on the BVRM. Simulation results show that the differences in the biases between the proposed method and the average rater method are small and that the empirical coverage probabilities of the proposed joint confidence regions are close to the nominal level. The proposed methods are illustrated using data from florbetapir F 18 positron emission tomographic imaging to predict the presence of β -amyloid in the brains of subjects with Alzheimer’s We an If each of exceeded , the was to otherwise, it was to zero. Similarly, if each element of the matrix for the specificities exceeded z p b ) , the outcome of the element was set to one; otherwise, it was set to zero. Here, z − p ) is the 100 p percentile of the standard distribution. our simulation study, 10,000 data sets were","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132468547","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}
H. Uehara, K. Satoh, Nagisa Komokata, Yohei Tokita, Mitsue Nishiyama, Maiko Iida, Junko Ishikawa, Kazuo Ogawa, Masahiro Yamamoto
In this article, we propose a strategy to show the combinability of multiple animal datasets in a parallel-line assay to estimate the relative potency. The following three assumptions are made in the linear fixed-effect modeling, and we examine if any of them result in nonconformance: For inferences about relative potency, a) is essential, and we derived a new metrics, intrasubject parallelism criterion (ISP), via the translation of aggregated individual bioequivalence criterion stated in the regulatory guidance (Food and Drug Administration, 2001). For b) and c), we used the 95% confidence interval of the I 2 criterion, which is commonly used to evaluate the interstudy homogeneity in a meta-analysis (Higgins and Thompson, 2002). For choosing the thresholds, we applied the conven-tions used in the guideline. The proposed procedure is demonstrated in an example analysis, and its properties are evaluated through a Monte Carlo simulation. The power of our proposed intrasubject parallelism criterion was shown to be high for designs of moderate size, but the demonstration of homogeneity via I 2 was rather conservative.
{"title":"Combinability of Animal Data in Relative Potency Estimations","authors":"H. Uehara, K. Satoh, Nagisa Komokata, Yohei Tokita, Mitsue Nishiyama, Maiko Iida, Junko Ishikawa, Kazuo Ogawa, Masahiro Yamamoto","doi":"10.5691/JJB.37.45","DOIUrl":"https://doi.org/10.5691/JJB.37.45","url":null,"abstract":"In this article, we propose a strategy to show the combinability of multiple animal datasets in a parallel-line assay to estimate the relative potency. The following three assumptions are made in the linear fixed-effect modeling, and we examine if any of them result in nonconformance: For inferences about relative potency, a) is essential, and we derived a new metrics, intrasubject parallelism criterion (ISP), via the translation of aggregated individual bioequivalence criterion stated in the regulatory guidance (Food and Drug Administration, 2001). For b) and c), we used the 95% confidence interval of the I 2 criterion, which is commonly used to evaluate the interstudy homogeneity in a meta-analysis (Higgins and Thompson, 2002). For choosing the thresholds, we applied the conven-tions used in the guideline. The proposed procedure is demonstrated in an example analysis, and its properties are evaluated through a Monte Carlo simulation. The power of our proposed intrasubject parallelism criterion was shown to be high for designs of moderate size, but the demonstration of homogeneity via I 2 was rather conservative.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132550838","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}
Anemia is a common complication of chronic kidney disease (CKD) and end-stage renal disease. A high hemoglobin level targeted in the treatment of anemia has been controversial because recent overseas studies have reported that it did not affect renal survival or increased the risk of cardiovascular events. In the motivation study, patients with CKD were randomly assigned to high or low hemoglobin target group (11.0–13.0 or 9.0–11.0 g/dL). The comparison of groups for the composite of renal events as the primary endpoint revealed no significant differences (p = 0.111). In these studies, ad hoc analyses suggested that a high hemoglobin level may potentially reduce cardiovascular events. However, those results could not precisely estimate the effect of treatment with high hemoglobin because of post-treatment selection bias. To address this problem, we used the method based on principal stratification approach to estimate the causal effect of Partial Responders by which the treatment effect of high hemoglobin can be evaluated. The results suggested that not only Partial but also Always Responders may benefit more from high hemoglobin treatment than Never Responders. These data suggest that patients with CKD can receive benefit from high hemoglobin treatment, who can respond to that treatment.
{"title":"Estimating Treatment Effect of High Hemoglobin Using the Principal Stratification Approach","authors":"J. Moriya, Y. Matsuyama","doi":"10.5691/JJB.37.7","DOIUrl":"https://doi.org/10.5691/JJB.37.7","url":null,"abstract":"Anemia is a common complication of chronic kidney disease (CKD) and end-stage renal disease. A high hemoglobin level targeted in the treatment of anemia has been controversial because recent overseas studies have reported that it did not affect renal survival or increased the risk of cardiovascular events. In the motivation study, patients with CKD were randomly assigned to high or low hemoglobin target group (11.0–13.0 or 9.0–11.0 g/dL). The comparison of groups for the composite of renal events as the primary endpoint revealed no significant differences (p = 0.111). In these studies, ad hoc analyses suggested that a high hemoglobin level may potentially reduce cardiovascular events. However, those results could not precisely estimate the effect of treatment with high hemoglobin because of post-treatment selection bias. To address this problem, we used the method based on principal stratification approach to estimate the causal effect of Partial Responders by which the treatment effect of high hemoglobin can be evaluated. The results suggested that not only Partial but also Always Responders may benefit more from high hemoglobin treatment than Never Responders. These data suggest that patients with CKD can receive benefit from high hemoglobin treatment, who can respond to that treatment.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124263766","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}
Kasumi Iwamoto, Ryo Tajiri, Keigo Fujikawa, T. Yanagawa
We consider usefulness of the second diagnostic test in medical diagnosis from the point of view of positive predictive value (PPV) and negative predictive value (NPV). We assume in this paper that medical diagnosis is given by the result of a single diagnostic test or group discussions of experts. We call the process the diagnostic test and consider the situation where an individual has chance to undergo two diagnostic tests. When the second diagnostic test is undertaken, two decision rules, Rule 1 and Rule 2, may be considered. Rule 1 is judge positive if the both tests are positive and negative otherwise. Rule 2 is judge negative if both tests are negative and positive otherwise. The test is called reasonable if, and only if it selects diseased person with higher probability than it does non-diseased persons. It is shown that when the first and second tests are reasonable, usefulness of the second test depends on one’s priority on PPV or NPV and whether one takes Rule 1 or Rule 2.
{"title":"Is the Second Independent Diagnostic Test in Medical Diagnosis Useful","authors":"Kasumi Iwamoto, Ryo Tajiri, Keigo Fujikawa, T. Yanagawa","doi":"10.5691/JJB.36.53","DOIUrl":"https://doi.org/10.5691/JJB.36.53","url":null,"abstract":"We consider usefulness of the second diagnostic test in medical diagnosis from the point of view of positive predictive value (PPV) and negative predictive value (NPV). We assume in this paper that medical diagnosis is given by the result of a single diagnostic test or group discussions of experts. We call the process the diagnostic test and consider the situation where an individual has chance to undergo two diagnostic tests. When the second diagnostic test is undertaken, two decision rules, Rule 1 and Rule 2, may be considered. Rule 1 is judge positive if the both tests are positive and negative otherwise. Rule 2 is judge negative if both tests are negative and positive otherwise. The test is called reasonable if, and only if it selects diseased person with higher probability than it does non-diseased persons. It is shown that when the first and second tests are reasonable, usefulness of the second test depends on one’s priority on PPV or NPV and whether one takes Rule 1 or Rule 2.","PeriodicalId":365545,"journal":{"name":"Japanese journal of biometrics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2016-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128514194","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}
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