Methods and applications of statistics in the life and health sciences
著者
書誌事項
Methods and applications of statistics in the life and health sciences
（Wiley series in methods and applications of statistics / advisory editor, N. Balakrishnan）
Wiley, c2010
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注記
Includes bibliographical references and index
Preface: "This is the first in a series of handbooks on methods and applications of statistics."
内容説明・目次
内容説明
Inspired by the Encyclopedia of Statistical Sciences, Second Edition, this volume outlines the statistical tools for successfully working with modern life and health sciences research
Data collection holds an essential part in dictating the future of health sciences and public health, as the compilation of statistics allows researchers and medical practitioners to monitor trends in health status, identify health problems, and evaluate the impact of health policies and programs. Methods and Applications of Statistics in the Life and Health Sciences serves as a single, one-of-a-kind resource on the wide range of statistical methods, techniques, and applications that are applied in modern life and health sciences in research. Specially designed to present encyclopedic content in an accessible and self-contained format, this book outlines thorough coverage of the underlying theory and standard applications to research in related disciplines such as biology, epidemiology, clinical trials, and public health.
Uniquely combining established literature with cutting-edge research, this book contains classical works and more than twenty-five new articles and completely revised contributions from the acclaimed Encyclopedia of Statistical Sciences, Second Edition. The result is a compilation of more than eighty articles that explores classic methodology and new topics, including:
Sequential methods in biomedical research
Statistical measures of human quality of life
Change-point methods in genetics
Sample size determination for clinical trials
Mixed-effects regression models for predicting pre-clinical disease
Probabilistic and statistical models for conception
Statistical methods are explored and applied to population growth, disease detection and treatment, genetic and genomic research, drug development, clinical trials, screening and prevention, and the assessment of rehabilitation, recovery, and quality of life. These topics are explored in contributions written by more than 100 leading academics, researchers, and practitioners who utilize various statistical practices, such as election bias, survival analysis, missing data techniques, and cluster analysis for handling the wide array of modern issues in the life and health sciences.
With its combination of traditional methodology and newly developed research, Methods and Applications of Statistics in the Life and Health Sciences has everything students, academics, and researchers in the life and health sciences need to build and apply their knowledge of statistical methods and applications.
目次
Preface v
Contributors vii
1 Aalen's Additive Risk Model 1
2 Aggregation 9
3 AIDS Stochastic Models 15
4 All-or-None Compliance 37
5 Ascertainment Sampling 43
6 Assessment Bias 47
7 Bioavailability and Bioequivalence 53
8 Cancer Stochastic Models 61
9 Centralized Genomic Control: A Simple Approach Correcting for Population Structures in Case-Control Association Studies 81
10 Change Point Methods in Genetics 95
11 Classical Biostatistics 117
12 Clinical Trials-II 131
13 Cluster Randomization 143
14 Cohort Analysis 157
15 Comparisons with a Control 167
16 Competing Risks 179
17 Countermatched Sampling 189
18 Counting Processes 193
19 Cox's Proportional Hazards Model 203
20 Crossover Trials 215
21 Design and Analysis for Repeated Measurements 225
22 DNA Fingerprinting 259
23 Epidemics 269
24 Epidemiological Statistics I 279
25 Epidemiological Statistics II 299
26 Event History Analysis 319
27 FDA Statistical Programs: An Overview 329
28 FDA Statistical Programs: Human Drugs 335
29 Follow-Up 343
30 Frailty Models 349
31 Framingham: An Evolving Longitudinal Study 353
32 Genetic Linkage 359
33 Group-Sequential Methods in Biomedical Research 365
34 Group-Sequential Tests 377
35 Grouped Data in Survival Analysis 391
36 Image Processing 397
37 Image Restoration and Reconstruction 415
38 Imputation and Multiple Imputation 425
39 Incomplete Data 441
40 Interval Censoring 451
41 Interrater Agreement 461
42 Kaplan-Meier Estimator I 481
43 Kaplan-Meier Estimator II 489
44 Landmark Data 501
45 Longitudinal Data Analysis 515
46 Meta-Analysis 531
47 Missing Data: Sensitivity Analysis 535
48 Multiple Testing in Clinical Trials 547
49 Mutation Processes 555
50 Nested Case-Control Sampling 559
51 Observational Studies 567
52 One- and Two-Armed Bandit Problems 573
53 Opthalmology 579
54 Panel Count Data 585
55 Planning and Analysis of Group-Randomized Trials 605
56 Predicting Preclinical Disease Using the Mixed-Effects Regression Model 613
57 Predicting Random Effects in Group-Randomized Trials 635
58 Probabilistic and Statistical Models for Conception 647
59 Probit Analysis 669
60 Prospective Studies 677
61 Quality Assessment for Clinical Trials 683
62 Repeated Measurements 695
63 Reproduction Rates 709
64 Retrospective Studies 713
65 Sample Size Determination for Clinical Trials 719
66 Scan Statistics 733
67 Semiparametric Analysis of Competing-Risk Data 749
68 Size and Shape Analysis 769
69 Stability Study Designs 781
70 Statistical Analysis of DNA Microarray Data 795
71 Statistical Genetics 801
72 Statistical Methods in Bioassay 807
73 Statistical Modeling of Human Fecundity 815
74 Statistical Quality of Life 839
75 Statistics at CDC 865
76 Statistics in Dentistry 871
77 Statistics in Evolutionary Genetics 873
78 Statistics in Forensic Science 879
79 Statistics in Human Genetics I 887
80 Statistics in Human Genetics II 893
81 Statistics in Medical Diagnosis 909
82 Statistics in Medicine 915
83 Statistics in the Pharmaceutical Industry 927
84 Statistics in Spatial Epidemiology 933
85 Stochastic Compartment Models 939
86 Surrogate Markers 945
87 Survival Analysis 953
Index 967
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