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  1. Article: Estimating a Change Point in a Sequence of Very High-Dimensional Covariance Matrices

    Dette, Holger / Pan, Guangming / Yang, Qing

    Journal of the American Statistical Association. 2022 Jan. 2, v. 117, no. 537

    2022  

    Abstract: This article considers the problem of estimating a change point in the covariance matrix in a sequence of high-dimensional vectors, where the dimension is substantially larger than the sample size. A two-stage approach is proposed to efficiently estimate ...

    Abstract This article considers the problem of estimating a change point in the covariance matrix in a sequence of high-dimensional vectors, where the dimension is substantially larger than the sample size. A two-stage approach is proposed to efficiently estimate the location of the change point. The first step consists of a reduction of the dimension to identify elements of the covariance matrices corresponding to significant changes. In a second step, we use the components after dimension reduction to determine the position of the change point. Theoretical properties are developed for both steps, and numerical studies are conducted to support the new methodology. Supplementary materials for this article are available online.
    Keywords Americans ; dimensions ; journals ; sample size ; variance covariance matrix
    Language English
    Dates of publication 2022-0102
    Size p. 444-454.
    Publishing place Taylor & Francis
    Document type Article
    ZDB-ID 2064981-2
    ISSN 1537-274X
    ISSN 1537-274X
    DOI 10.1080/01621459.2020.1785477
    Database NAL-Catalogue (AGRICOLA)

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  2. Article ; Online: Similarity of competing risks models with constant intensities in an application to clinical healthcare pathways involving prostate cancer surgery.

    Binder, Nadine / Möllenhoff, Kathrin / Sigle, August / Dette, Holger

    Statistics in medicine

    2022  Volume 41, Issue 19, Page(s) 3804–3819

    Abstract: The recent availability of routine medical data, especially in a university-clinical context, may enable the discovery of typical healthcare pathways, that is, typical temporal sequences of clinical interventions or hospital readmissions. However, such ... ...

    Abstract The recent availability of routine medical data, especially in a university-clinical context, may enable the discovery of typical healthcare pathways, that is, typical temporal sequences of clinical interventions or hospital readmissions. However, such pathways are heterogeneous in a large provider such as a university hospital, and it is important to identify similar care pathways that can still be considered typical pathways. We understand the pathway as a temporal process with possible transitions from a single initial treatment state to hospital readmission of different types, which constitutes a competing risks setting. In this article, we propose a multi-state model-based approach to uncover pathway similarity between two groups of individuals. We describe a new bootstrap procedure for testing the similarity of constant transition intensities from two competing risk models. In a large simulation study, we investigate the performance of our similarity approach with respect to different sample sizes and different similarity thresholds. The studies are motivated by an application from urological clinical routine and we show how the results can be transferred to the application example.
    MeSH term(s) Critical Pathways ; Delivery of Health Care ; Hospitals ; Humans ; Male ; Patient Readmission ; Prostatic Neoplasms/surgery
    Language English
    Publishing date 2022-06-13
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 843037-8
    ISSN 1097-0258 ; 0277-6715
    ISSN (online) 1097-0258
    ISSN 0277-6715
    DOI 10.1002/sim.9481
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1756: Show issues Location:
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    ab Jg. 2022: Lesesaal (EG)

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  3. Article: A Likelihood Ratio Approach to Sequential Change Point Detection for a General Class of Parameters

    Dette, Holger / Gösmann, Josua

    Journal of the American Statistical Association. 2020 July 2, v. 115, no. 531

    2020  

    Abstract: In this article, we propose a new approach for sequential monitoring of a general class of parameters of a d-dimensional time series, which can be estimated by approximately linear functionals of the empirical distribution function. We consider a closed- ... ...

    Abstract In this article, we propose a new approach for sequential monitoring of a general class of parameters of a d-dimensional time series, which can be estimated by approximately linear functionals of the empirical distribution function. We consider a closed-end method, which is motivated by the likelihood ratio test principle and compare the new method with two alternative procedures. We also incorporate self-normalization such that estimation of the long-run variance is not necessary. We prove that for a large class of testing problems the new detection scheme has asymptotic level α and is consistent. The asymptotic theory is illustrated for the important cases of monitoring a change in the mean, variance, and correlation. By means of a simulation study it is demonstrated that the new test performs better than the currently available procedures for these problems. Finally, the methodology is illustrated by a small data example investigating index prices from the dot-com bubble. Supplementary materials for this article are available online.
    Keywords mathematical theory ; time series analysis ; variance
    Language English
    Dates of publication 2020-0702
    Size p. 1361-1377.
    Publishing place Taylor & Francis
    Document type Article
    Note NAL-AP-2-clean
    ZDB-ID 2064981-2
    ISSN 1537-274X ; 0003-1291 ; 0162-1459
    ISSN (online) 1537-274X
    ISSN 0003-1291 ; 0162-1459
    DOI 10.1080/01621459.2019.1630562
    Database NAL-Catalogue (AGRICOLA)

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  4. Book ; Online: Towards active learning

    Schmalofski, Timo / Kroll, Martin / Dette, Holger / Janisch, Rebecca

    A stopping criterion for the sequential sampling of grain boundary degrees of freedom

    2023  

    Abstract: Many materials processes and properties depend on the anisotropy of the energy of grain boundaries, i.e. on the fact that this energy is a function of the five geometric degrees of freedom (DOF) of the grain boundaries. To access this parameter space in ... ...

    Abstract Many materials processes and properties depend on the anisotropy of the energy of grain boundaries, i.e. on the fact that this energy is a function of the five geometric degrees of freedom (DOF) of the grain boundaries. To access this parameter space in an efficient way and discover energy cusps in unexplored regions, a method was recently established, which combines atomistic simulations with statistical methods 10.1002/adts.202100615. This sequential sampling technique is now extended in the spirit of an active learning algorithm by adding a criterion to decide when the sampling is advanced enough to stop. To this instance, two parameters to analyse the sampling results on the fly are introduced: the number of cusps, which correspond to the most interesting and important regions of the energy landscape, and the maximum change of energy between two sequential iterations. Monitoring these two quantities provides valuable insight into how the subspaces are energetically structured. The combination of both parameters provides the necessary information to evaluate the sampling of the 2D subspaces of grain boundary plane inclinations of even non-periodic, low angle grain boundaries. With a reasonable number of datapoints in the initial design, only a few sequential iterations already influence the accuracy of the sampling substantially and the new algorithm outperforms regular high-throughput sampling.
    Keywords Condensed Matter - Materials Science ; Statistics - Methodology
    Subject code 669
    Publishing date 2023-02-03
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: Testing for similarity of binary efficacy-toxicity responses.

    Möllenhoff, Kathrin / Dette, Holger / Bretz, Frank

    Biostatistics (Oxford, England)

    2021  Volume 23, Issue 3, Page(s) 949–966

    Abstract: Clinical trials often aim to compare two groups of patients for efficacy and/or toxicity depending on covariates such as dose. Examples include the comparison of populations from different geographic regions or age classes or, alternatively, of different ...

    Abstract Clinical trials often aim to compare two groups of patients for efficacy and/or toxicity depending on covariates such as dose. Examples include the comparison of populations from different geographic regions or age classes or, alternatively, of different treatment groups. Similarity of these groups can be claimed if the difference in average outcome is below a certain margin over the entire covariate range. In this article, we consider the problem of testing for similarity in the case that efficacy and toxicity are measured as binary outcome variables. We develop a new test for the assessment of similarity of two groups for a single binary endpoint. Our approach is based on estimating the maximal deviation between the curves describing the responses of the two groups, followed by a parametric bootstrap test. Further, using a two-dimensional Gumbel-type model we develop methodology to establish similarity for (correlated) binary efficacy-toxicity outcomes. We investigate the operating characteristics of the proposed methodology by means of a simulation study and present a case study as an illustration.
    MeSH term(s) Computer Simulation ; Humans
    Language English
    Publishing date 2021-03-18
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2031500-4
    ISSN 1468-4357 ; 1465-4644
    ISSN (online) 1468-4357
    ISSN 1465-4644
    DOI 10.1093/biostatistics/kxaa058
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6259: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  6. Book ; Online ; Thesis: Mathematical machine learning with applications to biological data

    Huang, Shih-Ting [Verfasser] / Lederer, Johannes [Gutachter] / Dette, Holger [Gutachter]

    2022  

    Author's details Shih-Ting Huang ; Gutachter: Johannes Lederer, Holger Dette ; Fakultät für Mathematik
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language English
    Publisher Ruhr-Universität Bochum
    Publishing place Bochum
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

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  7. Book: Optimal designs for discriminating dose response models in toxicology studies

    Dette, Holger

    (Discussion paper / SFB 823 ; 2009,11)

    2009  

    Institution Sonderforschungsbereich Statistical Modelling of Nonlinear Dynamic Processes
    Author's details Holger Dette
    Series title Discussion paper / SFB 823 ; 2009,11
    Language English
    Size 21 S.
    Publisher SFB 823
    Publishing place Dortmund
    Document type Book
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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  8. Book: Asymptotic optimal designs under long-range dependence error structure

    Dette, Holger

    (Discussion paper / SFB 823 ; 2009,13)

    2009  

    Author's details Holger Dette
    Series title Discussion paper / SFB 823 ; 2009,13
    Language English
    Size 19 S.
    Publisher SFB 823
    Publishing place Dortmund
    Document type Book
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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  9. Book: Optimal designs for random effect models with correlated errors with applications in population pharmacokinetics

    Dette, Holger

    (Discussion paper / SFB 823 ; 2009,17)

    2009  

    Author's details Holger Dette
    Series title Discussion paper / SFB 823 ; 2009,17
    Language English
    Size 22 S., graph. Darst.
    Publisher SFB 823
    Publishing place Dortmund
    Document type Book
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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  10. Book: Optimal designs for estimating critical effective dose under model uncertainty in a dose response study

    Dette, Holger

    (Technical Report / Sonderforschungsbereich 475, Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund ; 2009,7)

    2009  

    Author's details Holger Dette
    Series title Technical Report / Sonderforschungsbereich 475, Komplexitätsreduktion in Multivariaten Datenstrukturen, Universität Dortmund ; 2009,7
    Language English
    Size 30 S.
    Publisher Univ., SFB 475
    Publishing place Dortmund
    Document type Book
    Database Library catalogue of the German National Library of Science and Technology (TIB), Hannover

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