Pub Date : 2019-11-16DOI: 10.1007/s40300-019-00162-5
Evženie Uglickich, I. Nagy, Dominika Vlčková
{"title":"Comparing clusterings using combination of the kappa statistic and entropy-based measure","authors":"Evženie Uglickich, I. Nagy, Dominika Vlčková","doi":"10.1007/s40300-019-00162-5","DOIUrl":"https://doi.org/10.1007/s40300-019-00162-5","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"253 - 270"},"PeriodicalIF":0.8,"publicationDate":"2019-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00162-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45212714","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 : 2019-10-30DOI: 10.1007/s40300-019-00161-6
S. Sinha
{"title":"Robust small area estimation in generalized linear mixed models","authors":"S. Sinha","doi":"10.1007/s40300-019-00161-6","DOIUrl":"https://doi.org/10.1007/s40300-019-00161-6","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"201 - 225"},"PeriodicalIF":0.8,"publicationDate":"2019-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00161-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45374955","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 : 2019-10-25DOI: 10.1007/s40300-019-00160-7
E. Schechtman, G. Schechtman
{"title":"The relationship between Gini terminology and the ROC curve","authors":"E. Schechtman, G. Schechtman","doi":"10.1007/s40300-019-00160-7","DOIUrl":"https://doi.org/10.1007/s40300-019-00160-7","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"171 - 178"},"PeriodicalIF":0.8,"publicationDate":"2019-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00160-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43821534","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 : 2019-09-28DOI: 10.1007/s40300-019-00159-0
D. Fouskakis
{"title":"Priors via imaginary training samples of sufficient statistics for objective Bayesian hypothesis testing","authors":"D. Fouskakis","doi":"10.1007/s40300-019-00159-0","DOIUrl":"https://doi.org/10.1007/s40300-019-00159-0","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"179 - 199"},"PeriodicalIF":0.8,"publicationDate":"2019-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00159-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46641276","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 : 2019-09-06DOI: 10.1007/s40300-022-00235-y
F. Din-Houn, D. Lau, S. Krumscheid
{"title":"Plateau proposal distributions for adaptive component-wise multiple-try metropolis","authors":"F. Din-Houn, D. Lau, S. Krumscheid","doi":"10.1007/s40300-022-00235-y","DOIUrl":"https://doi.org/10.1007/s40300-022-00235-y","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"80 1","pages":"343 - 370"},"PeriodicalIF":0.8,"publicationDate":"2019-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49358229","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 : 2019-08-17DOI: 10.1007/s40300-019-00158-1
Rajitha M. Silva, Yuping Guan, T. Swartz
{"title":"Bayesian treatment of non-standard problems in test analysis","authors":"Rajitha M. Silva, Yuping Guan, T. Swartz","doi":"10.1007/s40300-019-00158-1","DOIUrl":"https://doi.org/10.1007/s40300-019-00158-1","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"227 - 238"},"PeriodicalIF":0.8,"publicationDate":"2019-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00158-1","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49586024","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 : 2019-07-20DOI: 10.1007/s40300-019-00155-4
S. Chiappa, U. Paquet
{"title":"Unsupervised separation of dynamics from pixels","authors":"S. Chiappa, U. Paquet","doi":"10.1007/s40300-019-00155-4","DOIUrl":"https://doi.org/10.1007/s40300-019-00155-4","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"119 - 135"},"PeriodicalIF":0.8,"publicationDate":"2019-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00155-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44735242","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 : 2019-01-18DOI: 10.1007/s40300-019-00147-4
S. Provost, John N. Haddad
{"title":"A recursive approach for determining matrix inverses as applied to causal time series processes","authors":"S. Provost, John N. Haddad","doi":"10.1007/s40300-019-00147-4","DOIUrl":"https://doi.org/10.1007/s40300-019-00147-4","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"53 - 62"},"PeriodicalIF":0.8,"publicationDate":"2019-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00147-4","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52703424","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 : 2019-01-01Epub Date: 2019-05-30DOI: 10.1007/s40300-019-00151-8
Ruben Amoros, Ruth King, Hidenori Toyoda, Takashi Kumada, Philip J Johnson, Thomas G Bird
Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer deaths worldwide, and its early detection is a critical determinant of whether curative treatment is achievable. Early stage HCC is typically asymptomatic. Thus, screening programmes are used for cancer detection in patients at risk of tumour development. Radiological screening methods are limited by imperfect data, cost and associated risks, and additionally are unable to detect lesions until they have grown to a certain size. Therefore, some screening programmes use additional blood/serum biomarkers to help identify individuals in whom to target diagnostic cancer investigations. The GALAD score, combining the levels of several blood biomarkers, age and sex, has been developed to identify patients with early HCC. Here we propose a Bayesian hierarchical model for an individual's longitudinal GALAD scores whilst in HCC surveillance to identify potentially significant changes in the trend of the GALAD score, indicating the development of HCC, aiming to improve early detection compared to standard methods. An absorbent two-state continuous-time hidden Markov model is developed for the individual level longitudinal data where the states correspond to the presence/absence of HCC. The model is additionally informed by the information on the diagnosis by standard clinical practice, taking into account that HCC can be present before the actual diagnosis so that there may be false negatives within the diagnosis data. We fit the model to a Japanese cohort of patients undergoing HCC surveillance and show that the detection capability of this proposal is greater than using a fixed cut-point.
{"title":"A continuous-time hidden Markov model for cancer surveillance using serum biomarkers with application to hepatocellular carcinoma.","authors":"Ruben Amoros, Ruth King, Hidenori Toyoda, Takashi Kumada, Philip J Johnson, Thomas G Bird","doi":"10.1007/s40300-019-00151-8","DOIUrl":"10.1007/s40300-019-00151-8","url":null,"abstract":"<p><p>Hepatocellular carcinoma (HCC) is the fourth most common cause of cancer deaths worldwide, and its early detection is a critical determinant of whether curative treatment is achievable. Early stage HCC is typically asymptomatic. Thus, screening programmes are used for cancer detection in patients at risk of tumour development. Radiological screening methods are limited by imperfect data, cost and associated risks, and additionally are unable to detect lesions until they have grown to a certain size. Therefore, some screening programmes use additional blood/serum biomarkers to help identify individuals in whom to target diagnostic cancer investigations. The GALAD score, combining the levels of several blood biomarkers, age and sex, has been developed to identify patients with early HCC. Here we propose a Bayesian hierarchical model for an individual's longitudinal GALAD scores whilst in HCC surveillance to identify potentially significant changes in the trend of the GALAD score, indicating the development of HCC, aiming to improve early detection compared to standard methods. An absorbent two-state continuous-time hidden Markov model is developed for the individual level longitudinal data where the states correspond to the presence/absence of HCC. The model is additionally informed by the information on the diagnosis by standard clinical practice, taking into account that HCC can be present before the actual diagnosis so that there may be false negatives within the diagnosis data. We fit the model to a Japanese cohort of patients undergoing HCC surveillance and show that the detection capability of this proposal is greater than using a fixed cut-point.</p>","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"77 1","pages":"67-86"},"PeriodicalIF":0.8,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-019-00151-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42352686","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 : 2018-11-29DOI: 10.1007/s40300-018-0146-2
M. Ranalli, G. Montanari, Cecilia Vicarelli
{"title":"Estimation of small area counts with the benchmarking property","authors":"M. Ranalli, G. Montanari, Cecilia Vicarelli","doi":"10.1007/s40300-018-0146-2","DOIUrl":"https://doi.org/10.1007/s40300-018-0146-2","url":null,"abstract":"","PeriodicalId":51716,"journal":{"name":"Metron-International Journal of Statistics","volume":"76 1","pages":"349 - 378"},"PeriodicalIF":0.8,"publicationDate":"2018-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40300-018-0146-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52703403","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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