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  • UB Potsdam  (18)
  • SB Oranienburg
  • SB Ludwigsfelde
  • Inst. Menschenrechte
  • Hertie School
  • UdK Berlin
  • GB Grünheide
  • Chen, Ding-Geng  (18)
  • 1
    Online Resource
    Online Resource
    Advanced statistical methods in data science (2016)
    Singapore : Springer
    Details
    UID:
    b3kat_BV043990874
    Format: 1 Online-Ressource (XVI, 222 Seiten, 41 illus., 20 illus. in color)
    ISBN: 9789811025945
    Series Statement: ICSA book series in statistics
    Additional Edition: Erscheint auch als Druckausgabe ISBN 978-981-10-2593-8
    Language: English
    DOI: 10.1007/978-981-10-2594-5
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 2
    Online Resource
    Online Resource
    Statistical causal inferences and their applications in public health research (2016)
    [Cham] : Springer
    Details
    UID:
    b3kat_BV043857654
    Format: 1 Online-Ressource (XV, 321 Seiten, 24 illus., 11 illus. in color)
    ISBN: 9783319412597
    Series Statement: ICSA book series in statistics
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-41257-3
    Language: English
    Keywords: Aufsatzsammlung
    DOI: 10.1007/978-3-319-41259-7
    URL: Volltext  (URL des Erstveröffentlichers)
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    BTU Cottbus
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  • 3
    Online Resource
    Online Resource
    New frontiers of biostatistics and bioinformatics (2018)
    Cham : Springer
    Details
    UID:
    b3kat_BV045388735
    Format: 1 Online-Ressource (XXIV, 463 Seiten, 138 illus., 62 illus. in color)
    ISBN: 9783319993898
    Series Statement: ICSA book series in statistics
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-99388-1
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-99390-4
    Language: English
    DOI: 10.1007/978-3-319-99389-8
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 4
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    Online Resource
    Statistical analysis of microbiome data with R (2018)
    Singapore : Springer
    Details
    UID:
    b3kat_BV045238924
    Format: 1 Online-Ressource (XXIII, 505 Seiten, 84 illus., 67 illus. in color)
    ISBN: 9789811315343
    Series Statement: ICSA book series in statistics
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-131-533-6
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-131-535-0
    Language: English
    Keywords: Mikrobiom ; Statistik ; Programmiersprache
    DOI: 10.1007/978-981-13-1534-3
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  • 5
    Online Resource
    Online Resource
    Statistical regression modeling with R : longitudinal and multi-level modeling (2021)
    Cham : Springer
    Details
    UID:
    gbv_1756958629
    Format: 1 Online-Ressource (XVII, 228 Seiten)
    ISBN: 9783030675837
    Series Statement: Emerging topics in statistics and biostatistics
    Content: This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.
    Note: 1. Linear Regression -- 2. Introduction to Multi-Level Regression -- 3. Two-Level Multi-Level Modeling -- 4. Higher-Level Multi-Level Modeling -- 5. Longitudinal Data Analysis -- 6. Nonlinear Regression Modeling -- 7. Nonlinear Mixed-Effects Modeling -- 8. Generalized Linear Model -- 9. Generalized Multi-Level Model for Dichotomous Outcome -- 10. Generalized Multi-Level Model for Counts Outcome.
    Additional Edition: ISBN 9783030675820
    Additional Edition: ISBN 9783030675844
    Additional Edition: ISBN 9783030675851
    Additional Edition: Erscheint auch als Druck-Ausgabe Chen, Ding-Geng Statistical Regression Modeling with R Cham : Springer, 2021 ISBN 9783030675851
    Additional Edition: ISBN 9783030675820
    Language: English
    Subjects: Mathematics
    RVK:
    SK 840
    Keywords: Regressionsmodell
    DOI: 10.1007/978-3-030-67583-7
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    MPI Bildungsforschung
  • 6
    Online Resource
    Online Resource
    Statistical Methods for Global Health and Epidemiology : Principles, Methods and Applications (2020)
    Cham : Imprint: Springer
    Details
    UID:
    gbv_1697213332
    Format: 1 Online-Ressource (XV, 403 p. 161 illus., 129 illus. in color.)
    ISBN: 9783030352608
    Series Statement: ICSA book series in statistics
    Content: 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.
    Content: 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 with methods 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.
    Additional Edition: ISBN 9783030352592
    Additional Edition: ISBN 9783030352615
    Additional Edition: ISBN 9783030352622
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030352592
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030352615
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030352622
    Language: English
    DOI: 10.1007/978-3-030-35260-8
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  • 7
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    Online Resource
    Monte-Carlo Simulation-Based Statistical Modeling (2017)
    Singapore : Springer
    Details
    UID:
    gbv_1656684020
    Format: Online-Ressource (XVIII, 430 p. 64 illus., 33 illus. in color, online resource)
    ISBN: 9789811033070
    Series Statement: ICSA Book Series in Statistics
    Content: Part 1: Monte-Carlo Techniques -- 1. Overview of Monte-Carlo Techniques -- 2. On Improving the Efficiency of the Monte-Carlo Methods Using Ranked Simulated Approach -- 3. Joint generation of Different Types of Data with Specified Marginal and Association Structures for Simulation Purposes -- 4. Quantifying the Uncertainty in Optimal Experimental Schemes via Monte-Carlo Simulations -- 5. Normal and Non-normal Data Simulations for the Evaluation of Two-sample Location Tests -- 6. Understanding dichotomization from Monte-Carlo Simulations -- Part 2: Monte-Carlo Methods in Missing Data -- 7. Hybrid Monte-Carlo in Multiple Missing Data Imputations with Application to a Bone Fracture Data -- 8. Methods for Handling Incomplete Longitudinal Data due to Missing at Random Dropout -- 9. Applications of Simulation for Missing Data Issues in Longitudinal Clinical Trials -- 10. Application of Markov Chain Monte Carlo Multiple Imputation Method to Deal with Missing Data From the Mechanism of MNAR in Sensitivity Analysis for a Longitudinal Clinical Trial -- 11. Fully Bayesian Methods for Missing Data under Ignitability Assumption -- Part 3: Monte-Carlo in Statistical Modellings -- 12. Markov-Chain Monte-Carlo Methods in Statistical modelling -- 13. Monte-Carlo Simulation in Modeling for Hierarchical Linear Mixed Models -- 14. Monte-Carlo Simulation of Correlated Binary Responses -- 15. Monte Carlo Methods in Financial Modeling -- 16. Bayesian Intensive Computations in Elliptical Models
    Content: This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction
    Additional Edition: ISBN 9789811033063
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-10-3306-3
    Language: English
    DOI: 10.1007/978-981-10-3307-0
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  • 8
    Online Resource
    Online Resource
    Bayesian inference and computation in reliability and survival analysis (2022)
    Cham : Springer
    Details
    UID:
    gbv_181378650X
    Format: 1 Online-Ressource (xviii, 364 Seiten) , Illustrationen, Diagramme
    ISBN: 9783030886585
    Series Statement: Emerging Topics in Statistics and Biostatistics
    Content: 1. A Bayesian Approach for Step-stress Accelerated Life-tests for One-shot Devices under Exponential Distributions -- 2. Bayesian Estimation of Stress-strength Parameter for Moran-Downton Bivariate Exponential Distribution under Progressive Type-II Censoring -- 3. Bayesian Computation in A Birnbaum-Saunders Reliability Model with Applications to Fatigue Data -- 4. A Competing Risks Model Based on A Two-parameter Exponential Family Distribution under Progressive Type-II Censoring -- 5. Bayesian Computations for Reliability Analysis in Dynamic Environments -- 6. Bayesian Analysis of Stochastic Processes in Reliability -- 7. Bayesian Analysis of A New Bivariate Wiener Degradation Process -- 8. Bayesian Estimation for Bivariate Gamma Processes with Copula -- 9. Review of Statistical Treatment for Oncology Dose Escalation Trial with Prolonged Evaluation Window or Fast Enrollment -- 10. A Bayesian Approach for the Analysis of Tumorigenicity Data from Sacrificial Experiments under Weibull Lifetimes -- 11. Bayesian Sensitivity Analysis in Survival and Longitudinal Trial with Missing Data -- 12. Bayesian Analysis for Clustered Data under A Semi-competing Risks Framework -- 13. Survival Analysis for the Inverse Gaussian Distribution: Natural Conjugate and Jeffrey’s Priors -- 14. Bayesian Inferences for Panel Count Data and Interval-censored Data with Nonparametric Modeling of the Baseline Functions -- 15. Bayesian Approach for Interval-censored Survival Data with Time-varying Coefficients -- 16. Bayesian Approach for Joint-modeling Longitudinal Data and Survival Data Simultaneously in Public Health Studies.
    Content: Bayesian analysis is one of the important tools for statistical modelling and inference. Bayesian frameworks and methods have been successfully applied to solve practical problems in reliability and survival analysis, which have a wide range of real world applications in medical and biological sciences, social and economic sciences, and engineering. In the past few decades, significant developments of Bayesian inference have been made by many researchers, and advancements in computational technology and computer performance has laid the groundwork for new opportunities in Bayesian computation for practitioners. Because these theoretical and technological developments introduce new questions and challenges, and increase the complexity of the Bayesian framework, this book brings together experts engaged in groundbreaking research on Bayesian inference and computation to discuss important issues, with emphasis on applications to reliability and survival analysis. Topics covered are timely and have the potential to influence the interacting worlds of biostatistics, engineering, medical sciences, statistics, and more. The included chapters present current methods, theories, and applications in the diverse area of biostatistical analysis. The volume as a whole serves as reference in driving quality global health research. .
    Additional Edition: ISBN 9783030886578
    Additional Edition: ISBN 9783030886608
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030886578
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030886592
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030886608
    Language: English
    DOI: 10.1007/978-3-030-88658-5
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  • 9
    Online Resource
    Online Resource
    Innovative Statistical Methods for Public Health Data (2015)
    Cham : Springer International Publishing
    Details
    UID:
    gbv_1657914305
    Format: Online-Ressource (XIV, 351 p. 45 illus., 22 illus. in color, online resource)
    Edition: 1st ed. 2015
    ISBN: 9783319185361
    Series Statement: ICSA Book Series in Statistics
    Content: Part 1: Modelling Clustered Data -- Methods for Analyzing Secondary Outcomes in Public Health Case Control Studies -- Controlling for Population Density Using Clustering and Data Weighting Techniques When Examining Social Health and Welfare Problems -- On the Inference of Partially Correlated Data with Applications to Public Health Issues -- Modeling Time-Dependent Covariates in Longitudinal Data Analyses -- Solving Probabilistic Discrete Event Systems with Moore-Penrose Generalized Inverse Matrix Method to Extract Longitudinal Characteristics from Cross-Sectional Survey Data -- Part II: Modelling Incomplete or Missing Data -- On the Effects of Structural Zeros in Regression Models -- Modeling Based on Progressively Type-I Interval Censored Sample -- Techniques for Analyzing Incomplete Data in Public Health Research -- A Continuous Latent Factor Model for Non-ignorable Missing Data -- Part III: Healthcare Research Models -- Health Surveillance -- Standardization and Decomposition Analysis: A Useful Analytical Method for Outcome Difference, Inequality and Disparity Studies -- Cusp Catastrophe Modeling in Medical and Health Research -- On Ranked Set Sampling Variation and its Applications to Public Health Research -- Weighted Multiple Testing Correction for Correlated Endpoints in Survival Data -- Meta-analytic Methods for Public Health Research
    Content: The book brings together experts working in public health and multi-disciplinary areas to present recent issues in statistical methodological development and their applications. This timely book will impact model development and data analyses of public health research across a wide spectrum of analysis. Data and software used in the studies are available for the reader to replicate the models and outcomes. The fifteen chapters range in focus from techniques for dealing with missing data with Bayesian estimation, health surveillance and population definition and implications in applied latent class analysis, to multiple comparison and meta-analysis in public health data. Researchers in biomedical and public health research will find this book to be a useful reference, and it can be used in graduate level classes
    Note: Include bibliographical references and index , Part 1: Modelling Clustered DataMethods for Analyzing Secondary Outcomes in Public Health Case Control Studies -- Controlling for Population Density Using Clustering and Data Weighting Techniques When Examining Social Health and Welfare Problems -- On the Inference of Partially Correlated Data with Applications to Public Health Issues -- Modeling Time-Dependent Covariates in Longitudinal Data Analyses -- Solving Probabilistic Discrete Event Systems with Moore-Penrose Generalized Inverse Matrix Method to Extract Longitudinal Characteristics from Cross-Sectional Survey Data -- Part II: Modelling Incomplete or Missing Data -- On the Effects of Structural Zeros in Regression Models -- Modeling Based on Progressively Type-I Interval Censored Sample -- Techniques for Analyzing Incomplete Data in Public Health Research -- A Continuous Latent Factor Model for Non-ignorable Missing Data -- Part III: Healthcare Research Models -- Health Surveillance -- Standardization and Decomposition Analysis: A Useful Analytical Method for Outcome Difference, Inequality and Disparity Studies -- Cusp Catastrophe Modeling in Medical and Health Research -- On Ranked Set Sampling Variation and its Applications to Public Health Research -- Weighted Multiple Testing Correction for Correlated Endpoints in Survival Data -- Meta-analytic Methods for Public Health Research.
    Additional Edition: ISBN 9783319185354
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-18535-4
    Additional Edition: Erscheint auch als Druck-Ausgabe Innovative statistical methods for public health data Cham [u.a.] : Springer, 2015 ISBN 9783319185354
    Additional Edition: ISBN 9783319185361
    Language: English
    DOI: 10.1007/978-3-319-18536-1
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  • 10
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    Online Resource
    Biopharmaceutical Applied Statistics Symposium : Volume 2 Biostatistical Analysis of Clinical Trials (2018)
    Singapore : Springer Singapore
    Details
    UID:
    gbv_1030105634
    Format: Online-Ressource (XIII, 245 p. 34 illus., 18 illus. in color, online resource)
    Edition: Springer eBook Collection. Mathematics and Statistics
    ISBN: 9789811078262
    Series Statement: ICSA Book Series in Statistics
    Content: This BASS book Series publishes selected high-quality papers reflecting recent advances in the design and biostatistical analysis of biopharmaceutical experiments - particularly biopharmaceutical clinical trials. The papers were selected from invited presentations at the Biopharmaceutical Applied Statistics Symposium (BASS), which was founded by the first Editor in 1994 and has since become the premier international conference in biopharmaceutical statistics. The primary aims of the BASS are: 1) to raise funding to support graduate students in biostatistics programs, and 2) to provide an opportunity for professionals engaged in pharmaceutical drug research and development to share insights into solving the problems they encounter. The BASS book series is initially divided into three volumes addressing: 1) Design of Clinical Trials; 2) Biostatistical Analysis of Clinical Trials; and 3) Pharmaceutical Applications. This book is the second of the 3-volume book series. The topics covered include: Statistical Approaches to the Meta-analysis of Randomized Clinical Trials, Collaborative Targeted Maximum Likelihood Estimation to Assess Causal Effects in Observational Studies, Generalized Tests in Clinical Trials, Discrete Time-to-event and Score-based Methods with Application to Composite Endpoint for Assessing Evidence of Disease Activity-Free , Imputing Missing Data Using a Surrogate Biomarker: Analyzing the Incidence of Endometrial Hyperplasia, Selected Statistical Issues in Patient-reported Outcomes, Network Meta-analysis, Detecting Safety Signals Among Adverse Events in Clinical Trials, Applied Meta-analysis Using R, Treatment of Missing Data in Comparative Effectiveness Research, Causal Estimands: A Common Language for Missing Data, Bayesian Subgroup Analysis with Examples, Statistical Methods in Diagnostic Devices, A Question-Based Approach to the Analysis of Safety Data, Analysis of Two-stage Adaptive Seamless Trial Design, and Multiplicity Problems in Clinical Trials - A Regulatory Perspective
    Content: On Statistical Approaches to Meta-analysis of Randomized Clinical Trials -- Collaborative Targeted Maximum Likelihood Estimation to Assess Causal Effects in Observational Studies -- Generalized Tests in Clinical Trials -- Discrete Time-to-event and Score-based Methods with Application to Composite Endpoint for Assessing Evidence of Disease Activity-Free -- Imputing Missing Data Using a Surrogate Biomarker: Analyzing the Incidence of Endometrial Hyperplasia -- Some Statistical Issues in Patient-reported Outcomes -- Network Meta-analysis -- Detecting Safety Signals Among Adverse Events in Clinical Trials -- Applied Meta-analysis using R -- Treatment of Missing Data in Comparative Effectiveness Research -- Missing Data -- Bayesian Subgroup Analysis with Examples -- Statistical Methods in Diagnostic Devices -- A Question-Based Approach to the Analysis of Safety Data -- Analysis of Two-stage Adaptive Seamless Trial Design -- Multiplicity Problems in Clinical Trials - A Regulatory Perspective
    Additional Edition: ISBN 9789811078255
    Additional Edition: ISBN 9789811078279
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-10-7825-5
    Additional Edition: Printed edition ISBN 9789811078255
    Additional Edition: Printed edition ISBN 9789811078279
    Language: English
    DOI: 10.1007/978-981-10-7826-2
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