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  1. Book ; Online ; E-Book: Applied surrogate endpoint evaluation methods with SAS and R

    Alonso Abad, Ariel

    (Chapman & Hall/CRC biostatistics series)

    2017  

    Author's details Ariel Alonso [und 8 weitere]
    Series title Chapman & Hall/CRC biostatistics series
    Keywords Biomarkers ; Models, Theoretical ; Clinical Trials as Topic / methods ; Statistics as Topic / methods ; Programming Languages
    Subject code 610.72
    Language English
    Size 1 Online-Ressource (xxi, 373 Seiten), Illustrationen
    Publisher CRC Press, Taylor & Francis Group
    Publishing place Boca Raton
    Publishing country United States
    Document type Book ; Online ; E-Book
    Remark Zugriff für angemeldete ZB MED-Nutzerinnen und -Nutzer
    HBZ-ID HT019502665
    ISBN 978-1-4822-4937-8 ; 9781482249361 ; 1-4822-4937-5 ; 1482249367
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article ; Online: A joint penalized spline smoothing model for the number of positive and negative COVID-19 tests.

    De Witte, Dries / Abad, Ariel Alonso / Neyens, Thomas / Verbeke, Geert / Molenberghs, Geert

    PloS one

    2024  Volume 19, Issue 5, Page(s) e0303254

    Abstract: One of the key tools to understand and reduce the spread of the SARS-CoV-2 virus is testing. The total number of tests, the number of positive tests, the number of negative tests, and the positivity rate are interconnected indicators and vary with time. ... ...

    Abstract One of the key tools to understand and reduce the spread of the SARS-CoV-2 virus is testing. The total number of tests, the number of positive tests, the number of negative tests, and the positivity rate are interconnected indicators and vary with time. To better understand the relationship between these indicators, against the background of an evolving pandemic, the association between the number of positive tests and the number of negative tests is studied using a joint modeling approach. All countries in the European Union, Switzerland, the United Kingdom, and Norway are included in the analysis. We propose a joint penalized spline model in which the penalized spline is reparameterized as a linear mixed model. The model allows for flexible trajectories by smoothing the country-specific deviations from the overall penalized spline and accounts for heteroscedasticity by allowing the autocorrelation parameters and residual variances to vary among countries. The association between the number of positive tests and the number of negative tests is derived from the joint distribution for the random intercepts and slopes. The correlation between the random intercepts and the correlation between the random slopes were both positive. This suggests that, when countries increase their testing capacity, both the number of positive tests and negative tests will increase. A significant correlation was found between the random intercepts, but the correlation between the random slopes was not significant due to a wide credible interval.
    MeSH term(s) Humans ; COVID-19/epidemiology ; COVID-19/virology ; SARS-CoV-2/isolation & purification ; United Kingdom/epidemiology ; COVID-19 Testing/methods ; Norway/epidemiology ; Models, Statistical ; Switzerland/epidemiology ; Pandemics ; European Union
    Language English
    Publishing date 2024-05-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2267670-3
    ISSN 1932-6203 ; 1932-6203
    ISSN (online) 1932-6203
    ISSN 1932-6203
    DOI 10.1371/journal.pone.0303254
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  3. Article ; Online: Reflections on the concept of optimality of single decision point treatment regimes.

    Tran, Trung Dung / Abad, Ariel Alonso / Verbeke, Geert / Molenberghs, Geert / Van Mechelen, Iven

    Biometrical journal. Biometrische Zeitschrift

    2023  Volume 65, Issue 8, Page(s) e2200285

    Abstract: In many areas, applied researchers as well as practitioners have to choose between different solutions for a problem at hand; this calls for optimal decision rules to settle the choices involved. As a key example, one may think of the search for optimal ... ...

    Abstract In many areas, applied researchers as well as practitioners have to choose between different solutions for a problem at hand; this calls for optimal decision rules to settle the choices involved. As a key example, one may think of the search for optimal treatment regimes (OTRs) in clinical research, that specify which treatment alternative should be administered to each patient under study. Motivated by the fact that the concept of optimality of decision rules in general and treatment regimes in particular has received so far relatively little attention and discussion, we will present a number of reflections on it, starting from the basics of any optimization problem. Specifically, we will analyze the search space and the to be optimized criterion function underlying the search of single decision point OTRs, along with the many choice aspects that show up in their specification. Special attention is paid to formal characteristics and properties as well as to substantive concerns and hypotheses that may guide these choices. We illustrate with a few empirical examples taken from the literature. Finally, we discuss how the presented reflections may help sharpen statistical thinking about optimality of decision rules for treatment assignment and to facilitate the dialogue between the statistical consultant and the applied researcher in search of an OTR.
    Language English
    Publishing date 2023-09-21
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 131640-0
    ISSN 1521-4036 ; 0323-3847 ; 0006-3452
    ISSN (online) 1521-4036
    ISSN 0323-3847 ; 0006-3452
    DOI 10.1002/bimj.202200285
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    In stock of ZB MED Bonn / Germany

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  4. Article ; Online: A multivariate spatio-temporal model for the incidence of imported COVID-19 cases and COVID-19 deaths in Cuba.

    De Witte, Dries / Abad, Ariel Alonso / Molenberghs, Geert / Verbeke, Geert / Sanchez, Lizet / Mas-Bermejo, Pedro / Neyens, Thomas

    Spatial and spatio-temporal epidemiology

    2023  Volume 45, Page(s) 100588

    Abstract: To monitor the COVID-19 epidemic in Cuba, data on several epidemiological indicators have been collected on a daily basis for each municipality. Studying the spatio-temporal dynamics in these indicators, and how they behave similarly, can help us better ... ...

    Abstract To monitor the COVID-19 epidemic in Cuba, data on several epidemiological indicators have been collected on a daily basis for each municipality. Studying the spatio-temporal dynamics in these indicators, and how they behave similarly, can help us better understand how COVID-19 spread across Cuba. Therefore, spatio-temporal models can be used to analyze these indicators. Univariate spatio-temporal models have been thoroughly studied, but when interest lies in studying the association between multiple outcomes, a joint model that allows for association between the spatial and temporal patterns is necessary. The purpose of our study was to develop a multivariate spatio-temporal model to study the association between the weekly number of COVID-19 deaths and the weekly number of imported COVID-19 cases in Cuba during 2021. To allow for correlation between the spatial patterns, a multivariate conditional autoregressive prior (MCAR) was used. Correlation between the temporal patterns was taken into account by using two approaches; either a multivariate random walk prior was used or a multivariate conditional autoregressive prior (MCAR) was used. All models were fitted within a Bayesian framework.
    MeSH term(s) Humans ; COVID-19 ; Spatio-Temporal Analysis ; Incidence ; Bayes Theorem ; Cuba/epidemiology
    Language English
    Publishing date 2023-05-10
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 2515896-X
    ISSN 1877-5853 ; 1877-5845
    ISSN (online) 1877-5853
    ISSN 1877-5845
    DOI 10.1016/j.sste.2023.100588
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  5. Article ; Online: The individual-level surrogate threshold effect in a causal-inference setting with normally distributed endpoints.

    Van der Elst, Wim / Abad, Ariel Alonso / Coppenolle, Hans / Meyvisch, Paul / Molenberghs, Geert

    Pharmaceutical statistics

    2021  Volume 20, Issue 6, Page(s) 1216–1231

    Abstract: In the meta-analytic surrogate evaluation framework, the trial-level coefficient of ... ...

    Abstract In the meta-analytic surrogate evaluation framework, the trial-level coefficient of determination
    MeSH term(s) Biomarkers ; Causality ; Endpoint Determination ; Humans
    Chemical Substances Biomarkers
    Language English
    Publishing date 2021-05-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 2083706-9
    ISSN 1539-1612 ; 1539-1604
    ISSN (online) 1539-1612
    ISSN 1539-1604
    DOI 10.1002/pst.2141
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Generating random correlation matrices with fixed values: An application to the evaluation of multivariate surrogate endpoints

    Flórez, Alvaro Jóse / Abad, Ariel Alonso / Molenberghs, Geert / Van Der Elst, Wim

    Computational statistics & data analysis. 2019 Aug. 23,

    2019  

    Abstract: When assessing surrogate endpoints in clinical studies under a causal-inference framework, a simulation-based sensitivity analysis is required, so as to sample the unidentifiable parameters across plausible values. To be precise, correlation matrices ... ...

    Abstract When assessing surrogate endpoints in clinical studies under a causal-inference framework, a simulation-based sensitivity analysis is required, so as to sample the unidentifiable parameters across plausible values. To be precise, correlation matrices need to be sampled with only some of their entries identified from the data, known as the matrix completion problem. The positive-definiteness constraints are cumbersome functions involving all matrix entries, making this a challenging task. Some existing algorithms rely on sampling and then rejecting invalid solutions. A very efficient algorithm is built on previous work to generate large correlation matrices with some a prior fixed elements. The proposed methodology is applied to tackle a difficult problem in the surrogate marker field, namely, the evaluation of multivariate, potentially high-dimensional, surrogate endpoints. Whereas existing methods are limited to very low-dimensional surrogates, the new proposal is stable, fast, shows good properties, and is implemented in a user-friendly and freely available R package.
    Keywords algorithms ; clinical trials ; computer software
    Language English
    Dates of publication 2019-0823
    Publishing place Elsevier B.V.
    Document type Article
    Note Pre-press version
    ZDB-ID 1478763-5
    ISSN 0167-9473
    ISSN 0167-9473
    DOI 10.1016/j.csda.2019.106834
    Database NAL-Catalogue (AGRICOLA)

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  7. Article ; Online: A closed-form estimator for meta-analysis and surrogate markers evaluation.

    Flórez, Alvaro J / Molenberghs, Geert / Verbeke, Geert / Abad, Ariel Alonso

    Journal of biopharmaceutical statistics

    2018  Volume 29, Issue 2, Page(s) 318–332

    Abstract: Estimating complex linear mixed models using an iterative full maximum likelihood estimator can be cumbersome in some cases. With small and unbalanced datasets, convergence problems are common. Also, for large datasets, iterative procedures can be ... ...

    Abstract Estimating complex linear mixed models using an iterative full maximum likelihood estimator can be cumbersome in some cases. With small and unbalanced datasets, convergence problems are common. Also, for large datasets, iterative procedures can be computationally prohibitive. To overcome these computational issues, an unbiased two-stage closed-form estimator for the multivariate linear mixed model is proposed. It is rooted in pseudo-likelihood-based split-sample methodology and useful, for example, when evaluating normally distributed endpoints in a meta-analytic context. However, applications go well beyond this framework. Its statistical and computational performance is assessed via simulation. The method is applied to a study in schizophrenia.
    MeSH term(s) Algorithms ; Biomarkers ; Cluster Analysis ; Computer Simulation ; Endpoint Determination ; Humans ; Likelihood Functions ; Linear Models ; Meta-Analysis as Topic ; Models, Statistical ; Multivariate Analysis ; Randomized Controlled Trials as Topic/statistics & numerical data ; Research Design/statistics & numerical data ; Risperidone/administration & dosage ; Risperidone/adverse effects ; Risperidone/therapeutic use ; Schizophrenia/drug therapy ; Treatment Outcome
    Chemical Substances Biomarkers ; Risperidone (L6UH7ZF8HC)
    Language English
    Publishing date 2018-10-26
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1131763-2
    ISSN 1520-5711 ; 1054-3406
    ISSN (online) 1520-5711
    ISSN 1054-3406
    DOI 10.1080/10543406.2018.1535504
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 3511: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Testing for misspecification in generalized linear mixed models.

    Abad, Ariel Alonso / Litière, Saskia / Molenberghs, Geert

    Biostatistics (Oxford, England)

    2010  Volume 11, Issue 4, Page(s) 771–786

    Abstract: Generalized linear mixed models have become a frequently used tool for the analysis of non-Gaussian longitudinal data. Estimation is often based on maximum likelihood theory, which assumes that the underlying probability model is correctly specified. ... ...

    Abstract Generalized linear mixed models have become a frequently used tool for the analysis of non-Gaussian longitudinal data. Estimation is often based on maximum likelihood theory, which assumes that the underlying probability model is correctly specified. Recent research shows that the results obtained from these models are not always robust against departures from the assumptions on which they are based. Therefore, diagnostic tools for the detection of model misspecifications are of the utmost importance. In this paper, we propose 2 diagnostic tests that are based on 2 equivalent representations of the model information matrix. We evaluate the power of both tests using theoretical considerations as well as via simulation. In the simulations, the performance of the new tools is evaluated in many settings of practical relevance, focusing on misspecification of the random-effects structure. In all the scenarios, the results were encouraging, however, the tests also exhibited inflated Type I error rates when the sample size was small or moderate. Importantly, a parametric bootstrap version of the tests seems to overcome this problem, although more research in this direction may be needed. Finally, both tests were also applied to analyze a real case study in psychiatry.
    MeSH term(s) Algorithms ; Antipsychotic Agents/therapeutic use ; Bias ; Computer Simulation ; Humans ; Likelihood Functions ; Linear Models ; Longitudinal Studies/methods ; Randomized Controlled Trials as Topic ; Risperidone/therapeutic use ; Schizophrenia/drug therapy ; Software ; Treatment Outcome
    Chemical Substances Antipsychotic Agents ; Risperidone (L6UH7ZF8HC)
    Language English
    Publishing date 2010-10
    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/kxq019
    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:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  9. Article ; Online: Infectious diseases epidemiology, quantitative methodology, and clinical research in the midst of the COVID-19 pandemic: Perspective from a European country.

    Molenberghs, Geert / Buyse, Marc / Abrams, Steven / Hens, Niel / Beutels, Philippe / Faes, Christel / Verbeke, Geert / Van Damme, Pierre / Goossens, Herman / Neyens, Thomas / Herzog, Sereina / Theeten, Heidi / Pepermans, Koen / Abad, Ariel Alonso / Van Keilegom, Ingrid / Speybroeck, Niko / Legrand, Catherine / De Buyser, Stefanie / Hulstaert, Frank

    Contemporary clinical trials

    2020  Volume 99, Page(s) 106189

    Abstract: Starting from historic reflections, the current SARS-CoV-2 induced COVID-19 pandemic is examined from various perspectives, in terms of what it implies for the implementation of non-pharmaceutical interventions, the modeling and monitoring of the ... ...

    Abstract Starting from historic reflections, the current SARS-CoV-2 induced COVID-19 pandemic is examined from various perspectives, in terms of what it implies for the implementation of non-pharmaceutical interventions, the modeling and monitoring of the epidemic, the development of early-warning systems, the study of mortality, prevalence estimation, diagnostic and serological testing, vaccine development, and ultimately clinical trials. Emphasis is placed on how the pandemic had led to unprecedented speed in methodological and clinical development, the pitfalls thereof, but also the opportunities that it engenders for national and international collaboration, and how it has simplified and sped up procedures. We also study the impact of the pandemic on clinical trials in other indications. We note that it has placed biostatistics, epidemiology, virology, infectiology, and vaccinology, and related fields in the spotlight in an unprecedented way, implying great opportunities, but also the need to communicate effectively, often amidst controversy.
    MeSH term(s) Age Factors ; Biomedical Research/organization & administration ; Biomedical Research/standards ; Biostatistics/methods ; COVID-19/epidemiology ; COVID-19/mortality ; COVID-19 Testing/methods ; COVID-19 Testing/standards ; COVID-19 Vaccines ; Cause of Death ; Communicable Disease Control/organization & administration ; Drug Development/organization & administration ; Drug Industry/organization & administration ; Endpoint Determination/standards ; Epidemiologic Methods ; Europe ; Health Communication/standards ; Humans ; Immunity, Herd/physiology ; Models, Theoretical ; Pandemics ; Prevalence ; Public Opinion ; Randomized Controlled Trials as Topic/methods ; Randomized Controlled Trials as Topic/standards ; SARS-CoV-2 ; Seasons ; Sex Factors ; Time Factors
    Chemical Substances COVID-19 Vaccines
    Keywords covid19
    Language English
    Publishing date 2020-10-22
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2182176-8
    ISSN 1559-2030 ; 1551-7144
    ISSN (online) 1559-2030
    ISSN 1551-7144
    DOI 10.1016/j.cct.2020.106189
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1581: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  10. Article: Infectious diseases epidemiology, quantitative methodology, and clinical research in the midst of the COVID-19 pandemic: Perspective from a European country

    Molenberghs, Geert / Buyse, Marc / Abrams, Steven / Hens, Niel / Beutels, Philippe / Faes, Christel / Verbeke, Geert / Van Damme, Pierre / Goossens, Herman / Neyens, Thomas / Herzog, Sereina / Theeten, Heidi / Pepermans, Koen / Abad, Ariel Alonso / Van Keilegom, Ingrid / Speybroeck, Niko / Legrand, Catherine / De Buyser, Stefanie / Hulstaert, Frank

    Contemp Clin Trials

    Abstract: Starting from historic reflections, the current SARS-CoV-2 induced COVID-19 pandemic is examined from various perspectives, in terms of what it implies for the implementation of non-pharmaceutical interventions, the modeling and monitoring of the ... ...

    Abstract Starting from historic reflections, the current SARS-CoV-2 induced COVID-19 pandemic is examined from various perspectives, in terms of what it implies for the implementation of non-pharmaceutical interventions, the modeling and monitoring of the epidemic, the development of early-warning systems, the study of mortality, prevalence estimation, diagnostic and serological testing, vaccine development, and ultimately clinical trials. Emphasis is placed on how the pandemic had led to unprecedented speed in methodological and clinical development, the pitfalls thereof, but also the opportunities that it engenders for national and international collaboration, and how it has simplified and sped up procedures. We also study the impact of the pandemic on clinical trials in other indications. We note that it has placed biostatistics, epidemiology, virology, infectiology, and vaccinology, and related fields in the spotlight in an unprecedented way, implying great opportunities, but also the need to communicate effectively, often amidst controversy.
    Keywords covid19
    Publisher WHO
    Document type Article
    Note WHO #Covidence: #898554
    Database COVID19

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