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Autor Chen, (Din) Ding-Geng |
Documentos disponibles escritos por este autor (5)
Crear una solicitud de compra Refinar búsquedaComputational and Methodological Statistics and Biostatistics / Bekker, Andriëtte ; Chen, (Din) Ding-Geng ; Ferreira, Johannes T.
TÃtulo : Computational and Methodological Statistics and Biostatistics : Contemporary Essays in Advancement Tipo de documento: documento electrónico Autores: Bekker, Andriëtte, ; Chen, (Din) Ding-Geng, ; Ferreira, Johannes T., Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XXIV, 543 p. 116 ilustraciones, 96 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-42196-0 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: BiometrÃa Investigación cuantitativa Procesamiento de datos EstadÃsticas BioestadÃstica Análisis de datos y Big Data MinerÃa de datos y descubrimiento de conocimientos TeorÃa y métodos estadÃsticos. Clasificación: 570.15195 Resumen: En el ámbito estadÃstico, ciertos temas han recibido considerable atención durante la última década, debido al crecimiento y la evolución de los datos y los desafÃos teóricos. Este crecimiento ha ido invariablemente acompañado de avances computacionales, que han presentado tanto a los usuarios finales como a los investigadores las oportunidades necesarias para manejar datos e implementar soluciones de modelado con fines estadÃsticos. Este libro, que muestra la interacción entre una variedad de disciplinas, ofrece soluciones teóricas y aplicadas pioneras a problemas orientados a la práctica. Como colección cuidadosamente seleccionada de destacados lÃderes de pensamiento internacionales, fomenta la colaboración entre estadÃsticos y bioestadÃsticos y proporciona una variedad de procesos de pensamiento y herramientas a sus lectores. De este modo, el libro crea una comprensión y apreciación de los desarrollos recientes, asà como una implementación de estas contribuciones dentro del marco más amplio tanto de la academia como de la industria. La EstadÃstica y BioestadÃstica Computacional y Metodológica se compone de tres temas principales: • Desarrollos recientes en la teorÃa y aplicaciones de las distribuciones estadÃsticas; • Desarrollos recientes en modelización supervisada y no supervisada; • Avances recientes en bioestadÃstica; y también presenta código de programación y algoritmos adjuntos para permitir a los lectores replicar e implementar metodologÃas. Por lo tanto, esta monografÃa proporciona un punto de referencia conciso para una variedad de tendencias y temas actuales dentro del dominio estadÃstico. Con un atractivo interdisciplinario, será útil para investigadores, estudiantes de posgrado y profesionales de estadÃstica, bioestadÃstica, metodologÃa clÃnica, geologÃa, ciencia de datos y ciencia actuarial, entre otros. . Nota de contenido: 1. Computational Issues Of Maximum Likelihood Estimation Of The Skew-T Distribution And A Proposal For The Initialization Of Numerical Optimization - by Adelchi Azzalini (University of Padua, Italy) and Mahdi Salehi (University of Neyshabur, Iran) -- 2. Modelling Earthquakes: Characterizing Inter-Arrival Times And Magnitude - by Christophe Ley (Ghent University, Belgium) and Rosaria Simone (University of Naples Frederico II, Italy) -- 3. Multivariate Order Statistics Induced By Ordering Linear Combinations Of Components Of Multivariate Elliptical Random Vectors - by Ahad Jamalizadeh (Shahid Bahonar University, Iran), Roohollah Roozegar (Yasouj University, Iran), Narayanaswamy Balakrishnan (McMaster University, Canada) and Mehrdad Naderi (University of Pretoria, South Africa) -- 4. Spatial Interpolation Of Extreme PM1 Values Using Copulas - by Alfred Stein, Fakhereh Alidoost and Vera van Zoest (University of Twente, The Netherlands) -- 5. Distributional Aspects Of The Condition Number From A Unified Complex Wishart Setting - by Johannes Ferreira and Andriëtte Bekker (University of Pretoria, South Africa) -- 6. Weighted Bivariate Pólya-Aeppli Type Ii Distributions - by Claire Geldenhuys and René Ehlers (University of Pretoria, South Africa) -- 7. On The Distribution Of Linear Combinations Of Chi-Square Random Variables - by Carlos A. Coelho (Universidade Nova de Lisboa, Portugal) -- 8. Constructing Multivariate Distributions Using The Dirichlet As A Baseline - by Seite Makgai (University of Pretoria, South Africa), Mohammad Arashi (Shahrood University of Technology, Iran), Daan de Waal (University of the Free State), and Andriëtte Bekker (University of Pretoria, South Africa) -- 9. Evaluating Risk Measures Using The Normal Mean-Variance Birnbaum-Saunders Distribution - by Mehrdad Naderi (University of Pretoria, South Africa), Ahad Jamalizadeh (Shahid Bahonar University, Iran), Wan-Lun Wang (Feng Chia University, Taiwan), Tsung-I Lin (National Chung Hsing University, Taiwan) -- 10. On High-Dimensional Multivariate Bayesian Geostatistics - by Sudipto Banerjee (University of California, USA) -- 11. On Improving The Performance Of Logistic Regression Analysis Via Extreme Ranking - by Hani M. Samawi (Georgia Southern University, USA) -- 12. Optimal Sample Size Allocation For Multi-Level Stress Testing With Extreme Value Regression Under Time Censoring - by Ping Shing Chan (The Chinese University of Hong Kong, Hong Kong),Hon Yiu So (University of Waterloo, Canada), Hon Keung Tony Ng (Southern Methodist University, USA) and Wei Gao (Northeast Normal University, China) -- 13. Robust Mixtures Of Scale Mixtures In The Exponential Family - by Frans Kanfer and Sollie Millard (University of Pretoria, South Africa) -- 14. Variable Selection Of Interval-Censored Failure Time Data - by Tony Sun (University of Missouri, USA) -- 15. On The Design Of A Platform Trial For The Treatment Of Recurrent Clostridium Difficile Infection By Fecal Microbiota Transplantation - by Christine H. Lee (Royal Jubilee Hospital, Canada), Dina Kao (University of Alberta, Canada), Theodore Steiner (University of Vancouver, Canada), Augustine Wigle (University of Guelph, Canada) and Peter T. Kim (University of Guelph, Canada) -- 16. Recent Advances In Bayesian Adaptive Designs And Applications - by J. Jack Lee (University of Texas, USA) -- 17. Generalizability Theory For Clinician-Rated Outcomes - by Joseph C. Cappelleri (Executive Director of Biostatistics, Pfizer Inc) -- 18. Simultaneous Variable Selection And Estimation In Generalized Semiparametric Mixed Effect Modeling Of Longitudinal Data - by Mozhgan Taavoni and Mohammad Arashi (Shahrood University of Technology, Iran) -- 19. Generalized Rayleigh-Exponential-Weibull Distribution and its Application to Modelling of Progressive Type-I Interval Censored Data - by Ding-Geng Chen (University of Pretoria) and Y. L. Lio (University of South Dakota) -- 20. Applications Of Spatial Statistics In Poverty Alleviation In China- by Yong Ge (State Key Laboratory of Resources and Environmental Information System Institute of Geographical Sciences and Natural Resources Research, China) -- 21. Using Improved Robust Estimators In Semiparametric Models For High Dimensional Data - by Mahdi Roozbeh and Mina Norouzirad (Semnan University, Iran) -- 22. GMM marginal models with time dependent covariates - by Elsa Vazquez (Arizona State University) and Jeffrey R Wilson (Arizona State University). Tipo de medio : Computadora Summary : In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia andindustry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions; • Recent developments in supervised and unsupervised modelling; • Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Computational and Methodological Statistics and Biostatistics : Contemporary Essays in Advancement [documento electrónico] / Bekker, Andriëtte, ; Chen, (Din) Ding-Geng, ; Ferreira, Johannes T., . - 1 ed. . - [s.l.] : Springer, 2020 . - XXIV, 543 p. 116 ilustraciones, 96 ilustraciones en color.
ISBN : 978-3-030-42196-0
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: BiometrÃa Investigación cuantitativa Procesamiento de datos EstadÃsticas BioestadÃstica Análisis de datos y Big Data MinerÃa de datos y descubrimiento de conocimientos TeorÃa y métodos estadÃsticos. Clasificación: 570.15195 Resumen: En el ámbito estadÃstico, ciertos temas han recibido considerable atención durante la última década, debido al crecimiento y la evolución de los datos y los desafÃos teóricos. Este crecimiento ha ido invariablemente acompañado de avances computacionales, que han presentado tanto a los usuarios finales como a los investigadores las oportunidades necesarias para manejar datos e implementar soluciones de modelado con fines estadÃsticos. Este libro, que muestra la interacción entre una variedad de disciplinas, ofrece soluciones teóricas y aplicadas pioneras a problemas orientados a la práctica. Como colección cuidadosamente seleccionada de destacados lÃderes de pensamiento internacionales, fomenta la colaboración entre estadÃsticos y bioestadÃsticos y proporciona una variedad de procesos de pensamiento y herramientas a sus lectores. De este modo, el libro crea una comprensión y apreciación de los desarrollos recientes, asà como una implementación de estas contribuciones dentro del marco más amplio tanto de la academia como de la industria. La EstadÃstica y BioestadÃstica Computacional y Metodológica se compone de tres temas principales: • Desarrollos recientes en la teorÃa y aplicaciones de las distribuciones estadÃsticas; • Desarrollos recientes en modelización supervisada y no supervisada; • Avances recientes en bioestadÃstica; y también presenta código de programación y algoritmos adjuntos para permitir a los lectores replicar e implementar metodologÃas. Por lo tanto, esta monografÃa proporciona un punto de referencia conciso para una variedad de tendencias y temas actuales dentro del dominio estadÃstico. Con un atractivo interdisciplinario, será útil para investigadores, estudiantes de posgrado y profesionales de estadÃstica, bioestadÃstica, metodologÃa clÃnica, geologÃa, ciencia de datos y ciencia actuarial, entre otros. . Nota de contenido: 1. Computational Issues Of Maximum Likelihood Estimation Of The Skew-T Distribution And A Proposal For The Initialization Of Numerical Optimization - by Adelchi Azzalini (University of Padua, Italy) and Mahdi Salehi (University of Neyshabur, Iran) -- 2. Modelling Earthquakes: Characterizing Inter-Arrival Times And Magnitude - by Christophe Ley (Ghent University, Belgium) and Rosaria Simone (University of Naples Frederico II, Italy) -- 3. Multivariate Order Statistics Induced By Ordering Linear Combinations Of Components Of Multivariate Elliptical Random Vectors - by Ahad Jamalizadeh (Shahid Bahonar University, Iran), Roohollah Roozegar (Yasouj University, Iran), Narayanaswamy Balakrishnan (McMaster University, Canada) and Mehrdad Naderi (University of Pretoria, South Africa) -- 4. Spatial Interpolation Of Extreme PM1 Values Using Copulas - by Alfred Stein, Fakhereh Alidoost and Vera van Zoest (University of Twente, The Netherlands) -- 5. Distributional Aspects Of The Condition Number From A Unified Complex Wishart Setting - by Johannes Ferreira and Andriëtte Bekker (University of Pretoria, South Africa) -- 6. Weighted Bivariate Pólya-Aeppli Type Ii Distributions - by Claire Geldenhuys and René Ehlers (University of Pretoria, South Africa) -- 7. On The Distribution Of Linear Combinations Of Chi-Square Random Variables - by Carlos A. Coelho (Universidade Nova de Lisboa, Portugal) -- 8. Constructing Multivariate Distributions Using The Dirichlet As A Baseline - by Seite Makgai (University of Pretoria, South Africa), Mohammad Arashi (Shahrood University of Technology, Iran), Daan de Waal (University of the Free State), and Andriëtte Bekker (University of Pretoria, South Africa) -- 9. Evaluating Risk Measures Using The Normal Mean-Variance Birnbaum-Saunders Distribution - by Mehrdad Naderi (University of Pretoria, South Africa), Ahad Jamalizadeh (Shahid Bahonar University, Iran), Wan-Lun Wang (Feng Chia University, Taiwan), Tsung-I Lin (National Chung Hsing University, Taiwan) -- 10. On High-Dimensional Multivariate Bayesian Geostatistics - by Sudipto Banerjee (University of California, USA) -- 11. On Improving The Performance Of Logistic Regression Analysis Via Extreme Ranking - by Hani M. Samawi (Georgia Southern University, USA) -- 12. Optimal Sample Size Allocation For Multi-Level Stress Testing With Extreme Value Regression Under Time Censoring - by Ping Shing Chan (The Chinese University of Hong Kong, Hong Kong),Hon Yiu So (University of Waterloo, Canada), Hon Keung Tony Ng (Southern Methodist University, USA) and Wei Gao (Northeast Normal University, China) -- 13. Robust Mixtures Of Scale Mixtures In The Exponential Family - by Frans Kanfer and Sollie Millard (University of Pretoria, South Africa) -- 14. Variable Selection Of Interval-Censored Failure Time Data - by Tony Sun (University of Missouri, USA) -- 15. On The Design Of A Platform Trial For The Treatment Of Recurrent Clostridium Difficile Infection By Fecal Microbiota Transplantation - by Christine H. Lee (Royal Jubilee Hospital, Canada), Dina Kao (University of Alberta, Canada), Theodore Steiner (University of Vancouver, Canada), Augustine Wigle (University of Guelph, Canada) and Peter T. Kim (University of Guelph, Canada) -- 16. Recent Advances In Bayesian Adaptive Designs And Applications - by J. Jack Lee (University of Texas, USA) -- 17. Generalizability Theory For Clinician-Rated Outcomes - by Joseph C. Cappelleri (Executive Director of Biostatistics, Pfizer Inc) -- 18. Simultaneous Variable Selection And Estimation In Generalized Semiparametric Mixed Effect Modeling Of Longitudinal Data - by Mozhgan Taavoni and Mohammad Arashi (Shahrood University of Technology, Iran) -- 19. Generalized Rayleigh-Exponential-Weibull Distribution and its Application to Modelling of Progressive Type-I Interval Censored Data - by Ding-Geng Chen (University of Pretoria) and Y. L. Lio (University of South Dakota) -- 20. Applications Of Spatial Statistics In Poverty Alleviation In China- by Yong Ge (State Key Laboratory of Resources and Environmental Information System Institute of Geographical Sciences and Natural Resources Research, China) -- 21. Using Improved Robust Estimators In Semiparametric Models For High Dimensional Data - by Mahdi Roozbeh and Mina Norouzirad (Semnan University, Iran) -- 22. GMM marginal models with time dependent covariates - by Elsa Vazquez (Arizona State University) and Jeffrey R Wilson (Arizona State University). Tipo de medio : Computadora Summary : In the statistical domain, certain topics have received considerable attention during the last decade or so, necessitated by the growth and evolution of data and theoretical challenges. This growth has invariably been accompanied by computational advancement, which has presented end users as well as researchers with the necessary opportunities to handle data and implement modelling solutions for statistical purposes. Showcasing the interplay among a variety of disciplines, this book offers pioneering theoretical and applied solutions to practice-oriented problems. As a carefully curated collection of prominent international thought leaders, it fosters collaboration between statisticians and biostatisticians and provides an array of thought processes and tools to its readers. The book thereby creates an understanding and appreciation of recent developments as well as an implementation of these contributions within the broader framework of both academia andindustry. Computational and Methodological Statistics and Biostatistics is composed of three main themes: • Recent developments in theory and applications of statistical distributions; • Recent developments in supervised and unsupervised modelling; • Recent developments in biostatistics; and also features programming code and accompanying algorithms to enable readers to replicate and implement methodologies. Therefore, this monograph provides a concise point of reference for a variety of current trends and topics within the statistical domain. With interdisciplinary appeal, it will be useful to researchers, graduate students, and practitioners in statistics, biostatistics, clinical methodology, geology, data science, and actuarial science, amongst others. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Design and Analysis of Subgroups with Biopharmaceutical Applications Tipo de documento: documento electrónico Autores: Ting, Naitee, ; Cappelleri, Joseph C., ; Ho, Shuyen, ; Chen, (Din) Ding-Geng, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XVIII, 400 p. 61 ilustraciones, 43 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-40105-4 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: BiometrÃa QuÃmica Farmaceútica BioestadÃstica Farmacia Clasificación: 57.015.195 Resumen: Este libro proporciona una descripción general de las teorÃas y aplicaciones sobre subgrupos en la industria biofarmacéutica. A partir de una variedad de perspectivas de expertos en la academia y la industria, esta colección ofrece un diálogo general sobre los avances recientes en aplicaciones biofarmacéuticas, nuevos desarrollos estadÃsticos y metodológicos y posibles direcciones futuras. El volumen cubre temas en subgrupos sobre el diseño de ensayos clÃnicos; identificación de subgrupos y medicina personalizada; y cuestiones generales en los análisis de subgrupos, incluidos los regulatorios. Los capÃtulos incluidos presentan métodos, teorÃas y aplicaciones de casos actuales en el diverso campo de aplicación y análisis de subgrupos. Al ofrecer perspectivas oportunas de una variedad de fuentes autorizadas, el volumen está diseñado para atraer a los profesionales de la industria farmacéutica y a estudiantes graduados e investigadores del mundo académico y gubernamental. Nota de contenido: 1. Data-driven and Confirmatory Subgroup Analysis in Clinical Trials -- 2. Subgroup Analysis – A View from Industry -- 3. Biomarker-Targeted Confirmatory Trials -- 4. Considerations on Subgroup Analysis in Design and Analysis of Multi-Regional Clinical Trials -- 5. Practical Subgroup Identification Strategies in Late-stage Clinical Trials -- 6. Exploratory Subgroup Identification for Biopharmaceutical Development -- 7. Logical Inference on Treatment Efficacy When Subgroup Exists -- 8. The GUIDE Approach to Subgroup Identification and Inference -- 9. Use of the VG (Virtual Twins Combined with GUIDE) Method in the Development of Precision Medicines -- 10. Subgroups Identification for Tailored Therapies: a System of Methods, a Framework for Consistent Methodology Evaluation, and an Integrated Learn-and-confirm Approach -- 11. Developing and Validating Predictive Classifiers in Randomized Clinical Trials -- 12. Issues Related to Subgroup Analysis -- 13. Subgroup Analysis with Partial Linear Model -- 14. Subgroup Analysis in the 21st Century -- 15. Power of Statistical Tests for Subgroup Analysis in Meta-Analysis -- 16. Heterogeneity and Subgroup Analysis in Network Meta-Analysis. Tipo de medio : Computadora Summary : This book provides an overview of the theories and applications on subgroups in the biopharmaceutical industry. Drawing from a range of expert perspectives in academia and industry, this collection offers an overarching dialogue about recent advances in biopharmaceutical applications, novel statistical and methodological developments, and potential future directions. The volume covers topics in subgroups in clinical trial design; subgroup identification and personalized medicine; and general issues in subgroup analyses, including regulatory ones. Included chapters present current methods, theories, and case applications in the diverse field of subgroup application and analysis. Offering timely perspectives from a range of authoritative sources, the volume is designed to have wide appeal to professionals in the pharmaceutical industry and to graduate students and researchers in academe and government. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Design and Analysis of Subgroups with Biopharmaceutical Applications [documento electrónico] / Ting, Naitee, ; Cappelleri, Joseph C., ; Ho, Shuyen, ; Chen, (Din) Ding-Geng, . - 1 ed. . - [s.l.] : Springer, 2020 . - XVIII, 400 p. 61 ilustraciones, 43 ilustraciones en color.
ISBN : 978-3-030-40105-4
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: BiometrÃa QuÃmica Farmaceútica BioestadÃstica Farmacia Clasificación: 57.015.195 Resumen: Este libro proporciona una descripción general de las teorÃas y aplicaciones sobre subgrupos en la industria biofarmacéutica. A partir de una variedad de perspectivas de expertos en la academia y la industria, esta colección ofrece un diálogo general sobre los avances recientes en aplicaciones biofarmacéuticas, nuevos desarrollos estadÃsticos y metodológicos y posibles direcciones futuras. El volumen cubre temas en subgrupos sobre el diseño de ensayos clÃnicos; identificación de subgrupos y medicina personalizada; y cuestiones generales en los análisis de subgrupos, incluidos los regulatorios. Los capÃtulos incluidos presentan métodos, teorÃas y aplicaciones de casos actuales en el diverso campo de aplicación y análisis de subgrupos. Al ofrecer perspectivas oportunas de una variedad de fuentes autorizadas, el volumen está diseñado para atraer a los profesionales de la industria farmacéutica y a estudiantes graduados e investigadores del mundo académico y gubernamental. Nota de contenido: 1. Data-driven and Confirmatory Subgroup Analysis in Clinical Trials -- 2. Subgroup Analysis – A View from Industry -- 3. Biomarker-Targeted Confirmatory Trials -- 4. Considerations on Subgroup Analysis in Design and Analysis of Multi-Regional Clinical Trials -- 5. Practical Subgroup Identification Strategies in Late-stage Clinical Trials -- 6. Exploratory Subgroup Identification for Biopharmaceutical Development -- 7. Logical Inference on Treatment Efficacy When Subgroup Exists -- 8. The GUIDE Approach to Subgroup Identification and Inference -- 9. Use of the VG (Virtual Twins Combined with GUIDE) Method in the Development of Precision Medicines -- 10. Subgroups Identification for Tailored Therapies: a System of Methods, a Framework for Consistent Methodology Evaluation, and an Integrated Learn-and-confirm Approach -- 11. Developing and Validating Predictive Classifiers in Randomized Clinical Trials -- 12. Issues Related to Subgroup Analysis -- 13. Subgroup Analysis with Partial Linear Model -- 14. Subgroup Analysis in the 21st Century -- 15. Power of Statistical Tests for Subgroup Analysis in Meta-Analysis -- 16. Heterogeneity and Subgroup Analysis in Network Meta-Analysis. Tipo de medio : Computadora Summary : This book provides an overview of the theories and applications on subgroups in the biopharmaceutical industry. Drawing from a range of expert perspectives in academia and industry, this collection offers an overarching dialogue about recent advances in biopharmaceutical applications, novel statistical and methodological developments, and potential future directions. The volume covers topics in subgroups in clinical trial design; subgroup identification and personalized medicine; and general issues in subgroup analyses, including regulatory ones. Included chapters present current methods, theories, and case applications in the diverse field of subgroup application and analysis. Offering timely perspectives from a range of authoritative sources, the volume is designed to have wide appeal to professionals in the pharmaceutical industry and to graduate students and researchers in academe and government. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates Tipo de documento: documento electrónico Autores: Wilson, Jeffrey R., ; Vazquez-Arreola, Elsa, ; Chen, (Din) Ding-Geng, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XXIII, 166 p. 20 ilustraciones ISBN/ISSN/DL: 978-3-030-48904-5 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: BiometrÃa EstadÃsticas administracion de servicios de salud Salud pública BioestadÃstica EstadÃstica en IngenierÃa FÃsica Informática QuÃmica y Ciencias de la Tierra TeorÃa y métodos estadÃsticos. Administración de salubridad Clasificación: 57.015.195 Resumen: Esta monografÃa proporciona un punto conciso de temas de investigación y referencias para modelar datos de respuesta correlacionados con covariables dependientes del tiempo y datos longitudinales para el análisis de modelos promediados por la población, destacando métodos de una variedad de académicos pioneros. Si bien los modelos presentados en el volumen se aplican a datos de salud y relacionados con la salud, se pueden utilizar para analizar cualquier tipo de datos que contengan covariables que cambien con el tiempo. Los datos incluidos se analizan con el uso de R y SAS, y los datos y los programas informáticos se proporcionan a los lectores para que puedan replicar e implementar los métodos cubiertos. Es un excelente recurso para los estudiosos de la estadÃstica y la bioestadÃstica tanto computacionales como metodológicas, particularmente en las áreas aplicadas de la salud. Nota de contenido: 1. Introduction to Binary Regression Models -- 2. Generalized Estimating Equations Binary Models -- 3. Lai and Small Models for Time-Dependent Covariates -- 4. Lalonde, wilson, and Yin Models for Time-Dependent Covariates -- 5. Irimata, Broatch, and Wilson Models for Time-Dependent Covariates -- 6. Bayesian GMM to IBW Method of Analysis -- 7. Models for Joint Responses for Time-Dependent Covariates -- 8. Other Models for Time-Dependent Covariates. Tipo de medio : Computadora Summary : This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Marginal Models in Analysis of Correlated Binary Data with Time Dependent Covariates [documento electrónico] / Wilson, Jeffrey R., ; Vazquez-Arreola, Elsa, ; Chen, (Din) Ding-Geng, . - 1 ed. . - [s.l.] : Springer, 2020 . - XXIII, 166 p. 20 ilustraciones.
ISBN : 978-3-030-48904-5
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: BiometrÃa EstadÃsticas administracion de servicios de salud Salud pública BioestadÃstica EstadÃstica en IngenierÃa FÃsica Informática QuÃmica y Ciencias de la Tierra TeorÃa y métodos estadÃsticos. Administración de salubridad Clasificación: 57.015.195 Resumen: Esta monografÃa proporciona un punto conciso de temas de investigación y referencias para modelar datos de respuesta correlacionados con covariables dependientes del tiempo y datos longitudinales para el análisis de modelos promediados por la población, destacando métodos de una variedad de académicos pioneros. Si bien los modelos presentados en el volumen se aplican a datos de salud y relacionados con la salud, se pueden utilizar para analizar cualquier tipo de datos que contengan covariables que cambien con el tiempo. Los datos incluidos se analizan con el uso de R y SAS, y los datos y los programas informáticos se proporcionan a los lectores para que puedan replicar e implementar los métodos cubiertos. Es un excelente recurso para los estudiosos de la estadÃstica y la bioestadÃstica tanto computacionales como metodológicas, particularmente en las áreas aplicadas de la salud. Nota de contenido: 1. Introduction to Binary Regression Models -- 2. Generalized Estimating Equations Binary Models -- 3. Lai and Small Models for Time-Dependent Covariates -- 4. Lalonde, wilson, and Yin Models for Time-Dependent Covariates -- 5. Irimata, Broatch, and Wilson Models for Time-Dependent Covariates -- 6. Bayesian GMM to IBW Method of Analysis -- 7. Models for Joint Responses for Time-Dependent Covariates -- 8. Other Models for Time-Dependent Covariates. Tipo de medio : Computadora Summary : This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Modern Statistical Methods for Health Research Tipo de documento: documento electrónico Autores: Zhao, Yichuan, ; Chen, (Din) Ding-Geng, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2021 Número de páginas: XXV, 496 p. 82 ilustraciones ISBN/ISSN/DL: 978-3-030-72437-5 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: BiometrÃa BiologÃa BioestadÃstica Investigación biomédica Clasificación: 57.015.195 Resumen: Este libro reúne las voces de destacados expertos en las fronteras de la bioestadÃstica, la biomedicina y las ciencias de la salud para discutir los procedimientos estadÃsticos, los métodos útiles y las aplicaciones novedosas en la investigación en bioestadÃstica. También incluye discusiones sobre posibles direcciones futuras de la biomedicina y nuevos desarrollos estadÃsticos para la investigación en salud, con la intención de estimular la investigación y fomentar las interacciones de los académicos en disciplinas relacionadas con la investigación en salud. Los temas cubiertos incluyen: Análisis de datos de salud y aplicaciones a datos de EHR Ensayos clÃnicos, FDR y aplicaciones en ciencias de la salud Análisis de grandes redes y sus aplicaciones en GWAS Análisis de supervivencia y análisis de datos funcionales Modelado gráfico en estudios genómicos El libro será valioso para los cientÃficos de datos y estadÃsticos que trabajan en biomedicina y salud, otros profesionales de las ciencias de la salud y estudiantes de posgrado e investigadores en bioestadÃstica y salud. Nota de contenido: 1. Alternative Capture-Recapture Point and Interval Estimators Based on Two Surveillance Streams – Lyles, Wilkinson, Williamson, Chen, Taylor, Jambai, Kaiser -- 2. On-Gaussian Model Based Object Tracking Analysis with Time Lapse Fluorescence Microscopy Images – Marcus, Kong -- 3. Detecting Changepoint in Gene Expressions over Time: An Application to Childhood Obesity – Mathur, Sung -- 4. How "Big" Are EHR Data? The Effective Sample Size of EHR Data Under Biased Sampling – Hubbard -- 5. A Nested Clustering Method to Detect and Cluster Transgenerational DNA Methylation Sites via Beta Regressions – Wang, Zhang, Han, Arshad, Karmaus -- 6. Controlling the False Discovery Rate of Grouped Hypotheses – MacDonald, Wilson, Liang, Qin -- 7. Approaches to Combining Phase II Proof-of-Concept and Dose-Finding Trials – Ting -- 8. On the Multiply Robust Estimation with Missing Data – Chen, Haziza -- 9. Recent Advances in Spectral Clustering and Their Applications in Bioinformatics – Xue -- 10. Functional DataModeling and Hypothesis Testing for Longitudinal Alzheimer Genome-Wide Association Studies – Li, Xu, Liu -- 11. Misuse of Classifiers in Biological Networks – Maharaj -- 12. A Selective Inference-based Two-stage Procedure for Clinical Safety Studies – Zhu, Guo -- 13. Inferring Stage of HCV Infections as Recent or Chronic by Machine Learning approach – Icer -- 14. Graphical Modeling of Multiple Biological Pathways in Genomic Studies – Cao, Zhang, Chen, Wang -- 15. Online Updating of Nonparametric Survival Estimator and Nonparametric Survival Test – Xue, Schifano, Hu -- 16. Mixed-Effects Negative Binomial Regression with Interval Censoring: A Simulation Study and Application to Precipitation and All-Cause Mortality Rates among Black South Africans over 1997-2013 – Landon, Lyles, Scovronick, Abadi, Bilotta, Hauer, Bell, Gribble -- 17. SAS Macros for Linear Mediation Analysis of Complex Survey Data Using Balanced Repeated Replication – Mai, Zhang -- 18. Joint Modeling of Multiple Skewed Longitudinal Processes with Excess of Zero and Time-to-Event: An Application to Fecundity Studies – Mirzaei, Kundu, Sundaram -- 19. Infectious Disease Epidemiology: Forecasting the Ongoing 2018-19 Ebola Epidemic in the Democratic Republic of Congo (DRC) Using Phenomenological Growth Models – Tariq, Chowell -- 20. Models and Estimation Methods for Item Factor Analysis: An Overview – Chen, Zhang. Tipo de medio : Computadora Summary : This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Modern Statistical Methods for Health Research [documento electrónico] / Zhao, Yichuan, ; Chen, (Din) Ding-Geng, . - 1 ed. . - [s.l.] : Springer, 2021 . - XXV, 496 p. 82 ilustraciones.
ISBN : 978-3-030-72437-5
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: BiometrÃa BiologÃa BioestadÃstica Investigación biomédica Clasificación: 57.015.195 Resumen: Este libro reúne las voces de destacados expertos en las fronteras de la bioestadÃstica, la biomedicina y las ciencias de la salud para discutir los procedimientos estadÃsticos, los métodos útiles y las aplicaciones novedosas en la investigación en bioestadÃstica. También incluye discusiones sobre posibles direcciones futuras de la biomedicina y nuevos desarrollos estadÃsticos para la investigación en salud, con la intención de estimular la investigación y fomentar las interacciones de los académicos en disciplinas relacionadas con la investigación en salud. Los temas cubiertos incluyen: Análisis de datos de salud y aplicaciones a datos de EHR Ensayos clÃnicos, FDR y aplicaciones en ciencias de la salud Análisis de grandes redes y sus aplicaciones en GWAS Análisis de supervivencia y análisis de datos funcionales Modelado gráfico en estudios genómicos El libro será valioso para los cientÃficos de datos y estadÃsticos que trabajan en biomedicina y salud, otros profesionales de las ciencias de la salud y estudiantes de posgrado e investigadores en bioestadÃstica y salud. Nota de contenido: 1. Alternative Capture-Recapture Point and Interval Estimators Based on Two Surveillance Streams – Lyles, Wilkinson, Williamson, Chen, Taylor, Jambai, Kaiser -- 2. On-Gaussian Model Based Object Tracking Analysis with Time Lapse Fluorescence Microscopy Images – Marcus, Kong -- 3. Detecting Changepoint in Gene Expressions over Time: An Application to Childhood Obesity – Mathur, Sung -- 4. How "Big" Are EHR Data? The Effective Sample Size of EHR Data Under Biased Sampling – Hubbard -- 5. A Nested Clustering Method to Detect and Cluster Transgenerational DNA Methylation Sites via Beta Regressions – Wang, Zhang, Han, Arshad, Karmaus -- 6. Controlling the False Discovery Rate of Grouped Hypotheses – MacDonald, Wilson, Liang, Qin -- 7. Approaches to Combining Phase II Proof-of-Concept and Dose-Finding Trials – Ting -- 8. On the Multiply Robust Estimation with Missing Data – Chen, Haziza -- 9. Recent Advances in Spectral Clustering and Their Applications in Bioinformatics – Xue -- 10. Functional DataModeling and Hypothesis Testing for Longitudinal Alzheimer Genome-Wide Association Studies – Li, Xu, Liu -- 11. Misuse of Classifiers in Biological Networks – Maharaj -- 12. A Selective Inference-based Two-stage Procedure for Clinical Safety Studies – Zhu, Guo -- 13. Inferring Stage of HCV Infections as Recent or Chronic by Machine Learning approach – Icer -- 14. Graphical Modeling of Multiple Biological Pathways in Genomic Studies – Cao, Zhang, Chen, Wang -- 15. Online Updating of Nonparametric Survival Estimator and Nonparametric Survival Test – Xue, Schifano, Hu -- 16. Mixed-Effects Negative Binomial Regression with Interval Censoring: A Simulation Study and Application to Precipitation and All-Cause Mortality Rates among Black South Africans over 1997-2013 – Landon, Lyles, Scovronick, Abadi, Bilotta, Hauer, Bell, Gribble -- 17. SAS Macros for Linear Mediation Analysis of Complex Survey Data Using Balanced Repeated Replication – Mai, Zhang -- 18. Joint Modeling of Multiple Skewed Longitudinal Processes with Excess of Zero and Time-to-Event: An Application to Fecundity Studies – Mirzaei, Kundu, Sundaram -- 19. Infectious Disease Epidemiology: Forecasting the Ongoing 2018-19 Ebola Epidemic in the Democratic Republic of Congo (DRC) Using Phenomenological Growth Models – Tariq, Chowell -- 20. Models and Estimation Methods for Item Factor Analysis: An Overview – Chen, Zhang. Tipo de medio : Computadora Summary : This book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Statistical Methods for Global Health and Epidemiology : Principles, Methods and Applications Tipo de documento: documento electrónico Autores: Chen, Xinguang, ; Chen, (Din) Ding-Geng, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2020 Número de páginas: XV, 413 p. 161 ilustraciones, 129 ilustraciones en color. ISBN/ISSN/DL: 978-3-030-35260-8 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: BiometrÃa EstadÃsticas EpidemiologÃa BioestadÃstica TeorÃa y métodos estadÃsticos. Clasificación: 57.015.195 Resumen: Este libro examina los métodos y modelos estadÃsticos utilizados en los campos de la salud global y la epidemiologÃa. Incluye métodos como el muestreo probabilÃstico innovador, la armonización y cifrado de datos y métodos avanzados descriptivos, analÃticos y de seguimiento. Se incluyen códigos de programa que utilizan R, asà como ejemplos de datos reales. La salud global contemporánea implica una mirÃada de desafÃos médicos y de salud, incluida la desigualdad de tratamiento, la epidemia de VIH/SIDA y su posterior control, la gripe, el control del tabaco, el uso de drogas y la contaminación ambiental. Además de sus vastas escalas y su perspectiva telescópica, abordar los problemas de salud global a menudo implica examinar poblaciones con recursos limitados y grandes diversidades geográficas y socioeconómicas. Por lo tanto, avanzar en la salud global requiere un nuevo diseño epidemiológico, nuevos datos y nuevos métodos de muestreo, procesamiento de datos y análisis estadÃstico. Este libro proporciona a los investigadores de salud global métodos que permitirán el acceso y la utilización de los datos existentes. Con contribuciones de académicos tanto en epidemiologÃa como en bioestadÃstica, este libro es un recurso práctico para investigadores, profesionales y estudiantes en la resolución de problemas de salud global en investigación, educación, capacitación y consulta. Nota de contenido: Existent Data Sources for Global Health and Epidemiology -- Satellite Imagery Data for Global Health and Epidemiology -- GIS/GPS-Assisted Probability Sampling in Resource-Limited Settings -- Construal-Level Theory Supported Methods for Sensitive Topics: Applications in Three Different Populations -- Integrative Data Analysis and Application in Global Health -- Introduction to Privacy-Preserving Data Collection and Sharing Methods for Global Health Research -- Geographic Mapping for Global Health Research -- A 4D-Indicator System of Count, P Rate, G Rate and PG Rate for Epidemiology and Global Health -- Historical Trends in Mortality Risk over a 100-Year Period in China with Recent Data-An Innovative Application of APC Modeling -- Moore-Penrose Generalized-Inverse Solution to APC Modeling for Historical Epidemiology and Global Health -- Mixed Effects Modeling of Multi-Site Data-Health Behaviors among Adolescents in Hong Kong, Macao, Taipei, Wuhan and Zhuhai -- Geographically Weighted Regression for Global Epidemiological Research -- Bayesian Spatial-Temporal Disease Modeling With Application to Malaria -- "Efficient Biosurveillance By A Statistical Process Control Chart Using Covariates" -- Cusp Catastrophe Regression Analysis of Testosterone in Bifurcating the Age-Related Changes in PSA, a Biomarker for Prostate Cancer -- Logistic Cusp Catastrophe Regression for Binary Outcome: Method Development and Empirical Testing. Tipo de medio : Computadora Summary : This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective, addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers withmethods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Statistical Methods for Global Health and Epidemiology : Principles, Methods and Applications [documento electrónico] / Chen, Xinguang, ; Chen, (Din) Ding-Geng, . - 1 ed. . - [s.l.] : Springer, 2020 . - XV, 413 p. 161 ilustraciones, 129 ilustraciones en color.
ISBN : 978-3-030-35260-8
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: BiometrÃa EstadÃsticas EpidemiologÃa BioestadÃstica TeorÃa y métodos estadÃsticos. Clasificación: 57.015.195 Resumen: Este libro examina los métodos y modelos estadÃsticos utilizados en los campos de la salud global y la epidemiologÃa. Incluye métodos como el muestreo probabilÃstico innovador, la armonización y cifrado de datos y métodos avanzados descriptivos, analÃticos y de seguimiento. Se incluyen códigos de programa que utilizan R, asà como ejemplos de datos reales. La salud global contemporánea implica una mirÃada de desafÃos médicos y de salud, incluida la desigualdad de tratamiento, la epidemia de VIH/SIDA y su posterior control, la gripe, el control del tabaco, el uso de drogas y la contaminación ambiental. Además de sus vastas escalas y su perspectiva telescópica, abordar los problemas de salud global a menudo implica examinar poblaciones con recursos limitados y grandes diversidades geográficas y socioeconómicas. Por lo tanto, avanzar en la salud global requiere un nuevo diseño epidemiológico, nuevos datos y nuevos métodos de muestreo, procesamiento de datos y análisis estadÃstico. Este libro proporciona a los investigadores de salud global métodos que permitirán el acceso y la utilización de los datos existentes. Con contribuciones de académicos tanto en epidemiologÃa como en bioestadÃstica, este libro es un recurso práctico para investigadores, profesionales y estudiantes en la resolución de problemas de salud global en investigación, educación, capacitación y consulta. Nota de contenido: Existent Data Sources for Global Health and Epidemiology -- Satellite Imagery Data for Global Health and Epidemiology -- GIS/GPS-Assisted Probability Sampling in Resource-Limited Settings -- Construal-Level Theory Supported Methods for Sensitive Topics: Applications in Three Different Populations -- Integrative Data Analysis and Application in Global Health -- Introduction to Privacy-Preserving Data Collection and Sharing Methods for Global Health Research -- Geographic Mapping for Global Health Research -- A 4D-Indicator System of Count, P Rate, G Rate and PG Rate for Epidemiology and Global Health -- Historical Trends in Mortality Risk over a 100-Year Period in China with Recent Data-An Innovative Application of APC Modeling -- Moore-Penrose Generalized-Inverse Solution to APC Modeling for Historical Epidemiology and Global Health -- Mixed Effects Modeling of Multi-Site Data-Health Behaviors among Adolescents in Hong Kong, Macao, Taipei, Wuhan and Zhuhai -- Geographically Weighted Regression for Global Epidemiological Research -- Bayesian Spatial-Temporal Disease Modeling With Application to Malaria -- "Efficient Biosurveillance By A Statistical Process Control Chart Using Covariates" -- Cusp Catastrophe Regression Analysis of Testosterone in Bifurcating the Age-Related Changes in PSA, a Biomarker for Prostate Cancer -- Logistic Cusp Catastrophe Regression for Binary Outcome: Method Development and Empirical Testing. Tipo de medio : Computadora Summary : This book examines statistical methods and models used in the fields of global health and epidemiology. It includes methods such as innovative probability sampling, data harmonization and encryption, and advanced descriptive, analytical and monitory methods. Program codes using R are included as well as real data examples. Contemporary global health involves a myriad of medical and health challenges, including inequality of treatment, the HIV/AIDS epidemic and its subsequent control, the flu, tobacco control, drug use, and environmental pollution. In addition to its vast scales and telescopic perspective, addressing global health concerns often involves examining resource-limited populations with large geographic, socioeconomic diversities. Therefore, advancing global health requires new epidemiological design, new data, and new methods for sampling, data processing, and statistical analysis. This book provides global health researchers withmethods that will enable access to and utilization of existing data. Featuring contributions from both epidemiological and biostatistical scholars, this book is a practical resource for researchers, practitioners, and students in solving global health problems in research, education, training, and consultation. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
