Contemporary Biostatistics with Biopharmaceutical Applications / / edited by Lanju Zhang, Ding-Geng (Din) Chen, Hongmei Jiang, Gang Li, Hui Quan |
Edizione | [1st ed. 2019.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
Descrizione fisica | 1 online resource (339 pages) |
Disciplina |
610.727
519.5 |
Collana | ICSA Book Series in Statistics |
Soggetto topico |
Statistics
Biostatistics Pharmaceutical technology Statistics for Life Sciences, Medicine, Health Sciences Statistical Theory and Methods Pharmaceutical Sciences/Technology |
ISBN | 3-030-15310-X |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Part I Biostatistical Methodology -- Dimension Reduction in High Dimensional Multivariate Time Series Analysis -- Multi-Panel Kendall Plot Applied to Measuring Dependence -- Flexible Optimal Design Strategies -- A Multivariate Spatial Modelling Approach with Nonparametric Cross-covariogram -- A Deterministic Global Optimization Method for Variational Inference -- Part II Statistical Genetics and Bioinformatics -- Subgroup identification with latent Dirichlet allocation -- Dictionary learning based genotype imputation to improve power for association testing -- Integrating Transcriptional Time Lag Information into Gene Regulatory Network Construction -- Optimal experimental designs for fMRI when the model matrix is uncertain -- On Exact and Approximate Distributions of K-homopolymer for iid and Markov Dependent DNA Sequences -- Part III Regulatory Statistics -- Utilizing Seamless Adaptive Designs for NASH Clinical Trials -- A Bayesian Non-inferiority Design with Companion Constancy Test in Active Controlled Trials -- A Study Design for Utilizing External Data to Augment the Control in a Randomized Controlled Trial -- Some thoughts in designing a Bayesian study: From a statistical reviewer’s perspective -- On Weighted Performance Goals in Medical Device Single-Arm Clinical Studies -- Part IV Biopharmaceutical Research and Applications.-Current Status Data in the Presence of a Terminal Event -- Seamless Phase 2/3 Study Design with an Oncology Example -- A Bayesian meta-analysis method for estimating risk difference of rare events -- Comparison of multi-arm multi-stage design and adaptive randomization in platform clinical trials -- A Calibrated Power Prior Approach to Borrow Information from Historical Data with Application -- A Gatekeeping Test in a Group Sequential Design with Multiple Interim Looks -- Application of Bayesian Methods in Oncology Dose Escalation Studies with Late Onset Toxicity -- Bayesian hierarchical model estimation and comparison of immunogenicity assay cut-points.-Inference for Two-Stage Dynamic Treatment Regimes in the Presence of Drop -- Comparison of different approaches for dynamic prediction of survival using longitudinal data -- Update on progress of ASA Biopharm Safety Monitoring Working Group -- Options for implementing pattern-mixture-based sensitivity analyses. |
Record Nr. | UNINA-9910349323603321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Innovative Statistical Methods for Public Health Data / / edited by Ding-Geng (Din) Chen, Jeffrey Wilson |
Edizione | [1st ed. 2015.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
Descrizione fisica | 1 online resource (354 p.) |
Disciplina | 362.1015195 |
Collana | ICSA Book Series in Statistics |
Soggetto topico |
Biometry
Public health Medicine - Research Biology - Research Biostatistics Public Health Biomedical Research |
ISBN | 3-319-18536-5 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 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. |
Record Nr. | UNINA-9910299767103321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Statistical Causal Inferences and Their Applications in Public Health Research / / edited by Hua He, Pan Wu, Ding-Geng (Din) Chen |
Edizione | [1st ed. 2016.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
Descrizione fisica | 1 online resource (XV, 321 p. 24 illus., 11 illus. in color.) |
Disciplina | 519.5 |
Collana | ICSA Book Series in Statistics |
Soggetto topico |
Statistics
Biostatistics Public health Statistics for Life Sciences, Medicine, Health Sciences Public Health |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Part I. Overview -- 1. Causal Inference – A Statistical Paradigm for Inferring Causality -- Part II. Propensity Score Method for Causal Inference -- 2. Overview of Propensity Score Methods -- 3. Sufficient Covariate, Propensity Variable and Doubly Robust Estimation -- 4. A Robustness Index of Propensity Score Estimation to Uncontrolled Confounders -- 5. Missing Confounder Data in Propensity Score Methods for Causal Inference -- 6. Propensity Score Modeling & Evaluation -- 7. Overcoming the Computing Barriers in Statistical Causal Inference -- Part III. Causal Inference in Randomized Clinical Studies -- 8. Semiparametric Theory and Empirical Processes in Causal Inference -- 9. Structural Nested Models for Cluster-Randomized Trials -- 10. Causal Models for Randomized Trials with Continuous Compliance -- 11. Causal Ensembles for Evaluating the Effect of Delayed Switch to Second-line Antiretroviral Regimens -- 12. Structural Functional Response Models for Complex Intervention Trials -- Part IV. Structural Equation Models for Mediation Analysis -- 13.Identification of Causal Mediation Models with An Unobserved Pre-treatment Confounder -- 14. A Comparison of Potential Outcome Approaches for Assessing Causal Mediation -- 15. Causal Mediation Analysis Using Structure Equation Models. . |
Record Nr. | UNINA-9910148857003321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Statistical Modeling for Degradation Data / / edited by Ding-Geng (Din) Chen, Yuhlong Lio, Hon Keung Tony Ng, Tzong-Ru Tsai |
Edizione | [1st ed. 2017.] |
Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 |
Descrizione fisica | 1 online resource (XVIII, 376 p. 109 illus., 67 illus. in color.) |
Disciplina | 519.5 |
Collana | ICSA Book Series in Statistics |
Soggetto topico |
Statistics
Statistical Theory and Methods Statistics for Business, Management, Economics, Finance, Insurance |
ISBN | 981-10-5194-1 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | I. Review and Theoretical Framework -- Chapter 1: Stochastic Accelerated Degradation Models Based on a Generalized Cumu-lative Damage Approach -- Chapter 2: Hierarchical Bayesian Change-Point Analysis for Nonlinear Degradation Data -- Chapter 3: Degradation Modeling, Analysis, and Applications on Residual Life Predic-tion -- Chapter 4: On Some Shock Models with Poisson and Generalized Poisson Shock Processes -- Chapter 5: Degradation Based Reliability Modeling and Assessment of Complex Systems in Dynamic Environments -- Chapter 6: A Survey of the Modeling and Applications on Non-Destructive and De-structive Degradation Tests -- II. Modeling and Experimental Designs -- Chapter 7: Degradation Test Plan for a Nonlinear Random-Coefficients Model -- Chapter 8: Optimal Designs for LED Degradation Modeling -- Chapter 9: Gamma Degradation Models: Inferences and Optimal Designs -- Chapter 10: Model Misspecification analysis of Inverse Gaussian and Gamma Degrada-tion Processes -- III. Applications -- Chapter 11: Practical Application of Fréchet Shock-Degradation Models for System Failures -- Chapter 12: Statistical Methods for Thermal Index Estimation Based on Accelerated Destructive Degradation Test Data -- Chapter 13: Inference on Remaining Useful Life Under Gamma Degradation Models with Random effects.-- Chapter 14: ADDT: An R Package for Analysis of Accelerated Destructive Degradation Test Data -- Chapter 15: Modeling and Inference of CD4 Data. . |
Record Nr. | UNINA-9910254306703321 |
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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Statistical Modeling in Biomedical Research [[electronic resource] ] : Contemporary Topics and Voices in the Field / / edited by Yichuan Zhao, Ding-Geng (Din) Chen |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (XVIII, 491 p. 107 illus., 79 illus. in color.) |
Disciplina | 570.15195 |
Collana | Emerging Topics in Statistics and Biostatistics |
Soggetto topico |
Statistics
Biostatistics Big data Data mining Statistics for Life Sciences, Medicine, Health Sciences Big Data/Analytics Data Mining and Knowledge Discovery |
ISBN | 3-030-33416-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Preface -- Part I: Next Generation Sequence Data Analysis -- 1. Modeling Species Specific Gene Expression Across Multiple Regions in the Brain -- 2. Classification of EEG Motion Artifact Signals Using Spatial ICA -- 3. Weighted K-means Clustering with Observation Weight for Single-cell Epigenomic Data -- 4. Discrete Multiple Testing in Detecting Differential Methylation Using Sequencing Data -- Part II: Deep Learning, Precision Medicine and Applications -- 5. Prediction of Functional Markers of Mass Cytometry Data via Deep Learning -- 6. Building Health Application Recommender System Using Partially Penalized Regression -- 7. Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data -- Part III: Large Scale Data Analysis and its Applications -- 8. Privacy Preserving Feature Selection Via Voted Wrapper Method For Horizontally Distributed Medical Data -- 9. Improving Maize Trait through Modifying Combination of Genes -- 10. Molecular Basis of Food Classification in Traditional Chinese Medicine -- 11. Discovery Among Binary Biomarkers in Heterogeneous Populations -- Part IV: Biomedical Research and the Modelling -- 12. Heat Kernel Smoothing on Manifolds and Its Application to Hyoid Bone Growth Modeling -- 13. Optimal Projections in the Distance-Based Statistical Methods -- 14. Kernel Tests for One, Two, and K-Sample Goodness-Of-Fit: State of the Art and Implementation Considerations -- 15. Hierarchical Modeling of the Effect of Pre-exposure Prophylaxis on HIV in the US -- 16. Mathematical Model of Mouse Ventricular Myocytes Overexpressing Adenylyl Cyclase Type 5 -- Part V: Survival Analysis with Complex Data Structure and its Applications -- 17. Non-Parametric Maximum Likelihood Estimator for Case-Cohort and Nested Case-Control Designs with Competing Risks Data -- Authors: Jie-Huei Wang, Chun-Hao Pan, Yi-Hau Chen and I-Shou Chang -- 18. Variable Selection in Partially Linear Proportional Hazards Model with Grouped Covariates and a Diverging Number of Parameters -- 19. Inference of Transition Probabilities in Multi-state Models using Adaptive Inverse Probability Censoring Weighting Technique. |
Record Nr. | UNISA-996418264403316 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
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Statistical Modeling in Biomedical Research : Contemporary Topics and Voices in the Field / / edited by Yichuan Zhao, Ding-Geng (Din) Chen |
Edizione | [1st ed. 2020.] |
Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
Descrizione fisica | 1 online resource (XVIII, 491 p. 107 illus., 79 illus. in color.) |
Disciplina | 570.15195 |
Collana | Emerging Topics in Statistics and Biostatistics |
Soggetto topico |
Biometry
Quantitative research Data mining Biostatistics Data Analysis and Big Data Data Mining and Knowledge Discovery |
ISBN | 3-030-33416-3 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Preface -- Part I: Next Generation Sequence Data Analysis -- 1. Modeling Species Specific Gene Expression Across Multiple Regions in the Brain -- 2. Classification of EEG Motion Artifact Signals Using Spatial ICA -- 3. Weighted K-means Clustering with Observation Weight for Single-cell Epigenomic Data -- 4. Discrete Multiple Testing in Detecting Differential Methylation Using Sequencing Data -- Part II: Deep Learning, Precision Medicine and Applications -- 5. Prediction of Functional Markers of Mass Cytometry Data via Deep Learning -- 6. Building Health Application Recommender System Using Partially Penalized Regression -- 7. Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Data -- Part III: Large Scale Data Analysis and its Applications -- 8. Privacy Preserving Feature Selection Via Voted Wrapper Method For Horizontally Distributed Medical Data -- 9. Improving Maize Trait through Modifying Combination of Genes -- 10. Molecular Basis of Food Classification in Traditional Chinese Medicine -- 11. Discovery Among Binary Biomarkers in Heterogeneous Populations -- Part IV: Biomedical Research and the Modelling -- 12. Heat Kernel Smoothing on Manifolds and Its Application to Hyoid Bone Growth Modeling -- 13. Optimal Projections in the Distance-Based Statistical Methods -- 14. Kernel Tests for One, Two, and K-Sample Goodness-Of-Fit: State of the Art and Implementation Considerations -- 15. Hierarchical Modeling of the Effect of Pre-exposure Prophylaxis on HIV in the US -- 16. Mathematical Model of Mouse Ventricular Myocytes Overexpressing Adenylyl Cyclase Type 5 -- Part V: Survival Analysis with Complex Data Structure and its Applications -- 17. Non-Parametric Maximum Likelihood Estimator for Case-Cohort and Nested Case-Control Designs with Competing Risks Data -- Authors: Jie-Huei Wang, Chun-Hao Pan, Yi-Hau Chen and I-Shou Chang -- 18. Variable Selection in Partially Linear Proportional Hazards Model with Grouped Covariates and a Diverging Number of Parameters -- 19. Inference of Transition Probabilities in Multi-state Models using Adaptive Inverse Probability Censoring Weighting Technique. |
Record Nr. | UNINA-9910483548903321 |
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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