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Author | : John M. Lachin |
Publisher | : John Wiley & Sons |
Total Pages | : 676 |
Release | : 2014-08-22 |
Genre | : Mathematics |
ISBN | : 1118625846 |
Download Biostatistical Methods Book in PDF, ePub and Kindle
Praise for the First Edition ". . . an excellent textbook . . . an indispensable reference for biostatisticians and epidemiologists." —International Statistical Institute A new edition of the definitive guide to classical and modern methods of biostatistics Biostatistics consists of various quantitative techniques that are essential to the description and evaluation of relationships among biologic and medical phenomena. Biostatistical Methods: The Assessment of Relative Risks, Second Edition develops basic concepts and derives an expanded array of biostatistical methods through the application of both classical statistical tools and more modern likelihood-based theories. With its fluid and balanced presentation, the book guides readers through the important statistical methods for the assessment of absolute and relative risks in epidemiologic studies and clinical trials with categorical, count, and event-time data. Presenting a broad scope of coverage and the latest research on the topic, the author begins with categorical data analysis methods for cross-sectional, prospective, and retrospective studies of binary, polychotomous, and ordinal data. Subsequent chapters present modern model-based approaches that include unconditional and conditional logistic regression; Poisson and negative binomial models for count data; and the analysis of event-time data including the Cox proportional hazards model and its generalizations. The book now includes an introduction to mixed models with fixed and random effects as well as expanded methods for evaluation of sample size and power. Additional new topics featured in this Second Edition include: Establishing equivalence and non-inferiority Methods for the analysis of polychotomous and ordinal data, including matched data and the Kappa agreement index Multinomial logistic for polychotomous data and proportional odds models for ordinal data Negative binomial models for count data as an alternative to the Poisson model GEE models for the analysis of longitudinal repeated measures and multivariate observations Throughout the book, SAS is utilized to illustrate applications to numerous real-world examples and case studies. A related website features all the data used in examples and problem sets along with the author's SAS routines. Biostatistical Methods, Second Edition is an excellent book for biostatistics courses at the graduate level. It is also an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.
Author | : Stephen W. Looney |
Publisher | : Springer Science & Business Media |
Total Pages | : 221 |
Release | : 2008-02-03 |
Genre | : Science |
ISBN | : 1592592422 |
Download Biostatistical Methods Book in PDF, ePub and Kindle
Leading biostatisticians and biomedical researchers describe many of the key techniques used to solve commonly occurring data analytic problems in molecular biology, and demonstrate how these methods can be used in the development of new markers for exposure to a risk factor or for disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, genetic susceptibility and association, evaluation of new biomarkers, and power analysis and sample size.
Author | : John M. Lachin |
Publisher | : John Wiley & Sons |
Total Pages | : 568 |
Release | : 2009-09-25 |
Genre | : Mathematics |
ISBN | : 0470317892 |
Download Biostatistical Methods Book in PDF, ePub and Kindle
Comprehensive coverage of classical and modern methods of biostatistics Biostatistical Methods focuses on the assessment of risks and relative risks on the basis of clinical investigations. It develops basic concepts and derives biostatistical methods through both the application of classical mathematical statistical tools and more modern likelihood-based theories. The first half of the book presents methods for the analysis of single and multiple 2x2 tables for cross-sectional, prospective, and retrospective (case-control) sampling, with and without matching using fixed and two-stage random effects models. The text then moves on to present a more modern likelihood- or model-based approach, which includes unconditional and conditional logistic regression; the analysis of count data and the Poisson regression model; and the analysis of event time data, including the proportional hazards and multiplicative intensity models. The book contains a technical appendix that presents the core mathematical statistical theory used for the development of classical and modern statistical methods. Biostatistical Methods: The Assessment of Relative Risks: * Presents modern biostatistical methods that are generalizations of the classical methods discussed * Emphasizes derivations, not just cookbook methods * Provides copious reference citations for further reading * Includes extensive problem sets * Employs case studies to illustrate application of methods * Illustrates all methods using the Statistical Analysis System(r) (SAS) Supplemented with numerous graphs, charts, and tables as well as a Web site for larger data sets and exercises, Biostatistical Methods: The Assessment of Relative Risks is an excellent guide for graduate-level students in biostatistics and an invaluable reference for biostatisticians, applied statisticians, and epidemiologists.
Author | : S. Selvin |
Publisher | : Brooks/Cole |
Total Pages | : 530 |
Release | : 1995 |
Genre | : Mathematics |
ISBN | : |
Download Practical Biostatistical Methods Book in PDF, ePub and Kindle
This text covers intermediate statistical methods in a practical and mathematically intuitive (no calculus) mode. It focuses on the following analysis methods useful to the researcher: linear regression, discriminant analysis, contingency tables, survival analysis, covariance, principal components, logistic regression and Poisson regression. Nonparametric methods are incorporated as needed.
Author | : Mark Chang |
Publisher | : Springer Science & Business Media |
Total Pages | : 316 |
Release | : 2011-07-15 |
Genre | : Medical |
ISBN | : 144199842X |
Download Modern Issues and Methods in Biostatistics Book in PDF, ePub and Kindle
Classic biostatistics, a branch of statistical science, has as its main focus the applications of statistics in public health, the life sciences, and the pharmaceutical industry. Modern biostatistics, beyond just a simple application of statistics, is a confluence of statistics and knowledge of multiple intertwined fields. The application demands, the advancements in computer technology, and the rapid growth of life science data (e.g., genomics data) have promoted the formation of modern biostatistics. There are at least three characteristics of modern biostatistics: (1) in-depth engagement in the application fields that require penetration of knowledge across several fields, (2) high-level complexity of data because they are longitudinal, incomplete, or latent because they are heterogeneous due to a mixture of data or experiment types, because of high-dimensionality, which may make meaningful reduction impossible, or because of extremely small or large size; and (3) dynamics, the speed of development in methodology and analyses, has to match the fast growth of data with a constantly changing face. This book is written for researchers, biostatisticians/statisticians, and scientists who are interested in quantitative analyses. The goal is to introduce modern methods in biostatistics and help researchers and students quickly grasp key concepts and methods. Many methods can solve the same problem and many problems can be solved by the same method, which becomes apparent when those topics are discussed in this single volume.
Author | : Dr Murray Logan |
Publisher | : John Wiley & Sons |
Total Pages | : 578 |
Release | : 2011-09-20 |
Genre | : Science |
ISBN | : 144436247X |
Download Biostatistical Design and Analysis Using R Book in PDF, ePub and Kindle
R — the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.
Author | : Shigeyuki Matsui |
Publisher | : Springer |
Total Pages | : 439 |
Release | : 2017-10-03 |
Genre | : Medical |
ISBN | : 981100126X |
Download Frontiers of Biostatistical Methods and Applications in Clinical Oncology Book in PDF, ePub and Kindle
This book presents the state of the art of biostatistical methods and their applications in clinical oncology. Many methodologies established today in biostatistics have been brought about through its applications to the design and analysis of oncology clinical studies. This field of oncology, now in the midst of evolution owing to rapid advances in biotechnologies and cancer genomics, is becoming one of the most promising disease fields in the shift toward personalized medicine. Modern developments of diagnosis and therapeutics of cancer have also been continuously fueled by recent progress in establishing the infrastructure for conducting more complex, large-scale clinical trials and observational studies. The field of cancer clinical studies therefore will continue to provide many new statistical challenges that warrant further progress in the methodology and practice of biostatistics. This book provides a systematic coverage of various stages of cancer clinical studies. Topics from modern cancer clinical trials include phase I clinical trials for combination therapies, exploratory phase II trials with multiple endpoints/treatments, and confirmative biomarker-based phase III trials with interim monitoring and adaptation. It also covers important areas of cancer screening, prognostic analysis, and the analysis of large-scale molecular data in the era of big data.
Author | : Stephen C. Newman |
Publisher | : John Wiley & Sons |
Total Pages | : 403 |
Release | : 2003-04-11 |
Genre | : Medical |
ISBN | : 0471461601 |
Download Biostatistical Methods in Epidemiology Book in PDF, ePub and Kindle
An introduction to classical biostatistical methods in epidemiology Biostatistical Methods in Epidemiology provides an introduction to a wide range of methods used to analyze epidemiologic data, with a focus on nonregression techniques. The text includes an extensive discussion of measurement issues in epidemiology, especially confounding. Maximum likelihood, Mantel-Haenszel, and weighted least squares methods are presented for the analysis of closed cohort and case-control data. Kaplan-Meier and Poisson methods are described for the analysis of censored survival data. A justification for using odds ratio methods in case-control studies is provided. Standardization of rates is discussed and the construction of ordinary, multiple decrement and cause-deleted life tables is outlined. Sample size formulas are given for a range of epidemiologic study designs. The text ends with a brief overview of logistic and Cox regression. Other highlights include: Many worked examples based on actual data Discussion of exact methods Recommendations for preferred methods Extensive appendices and references Biostatistical Methods in Epidemiology provides an excellent introduction to the subject for students, while also serving as a comprehensive reference for epidemiologists and other health professionals. For more information, visit www.wiley.com/mathematics
Author | : Stephen W. Looney |
Publisher | : Humana |
Total Pages | : 0 |
Release | : 2010-11-10 |
Genre | : Science |
ISBN | : 9781617372711 |
Download Biostatistical Methods Book in PDF, ePub and Kindle
Leading biostatisticians and biomedical researchers describe many of the key techniques used to solve commonly occurring data analytic problems in molecular biology, and demonstrate how these methods can be used in the development of new markers for exposure to a risk factor or for disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, genetic susceptibility and association, evaluation of new biomarkers, and power analysis and sample size.
Author | : Daniel Commenges |
Publisher | : CRC Press |
Total Pages | : 391 |
Release | : 2015-10-02 |
Genre | : Mathematics |
ISBN | : 1498729681 |
Download Dynamical Biostatistical Models Book in PDF, ePub and Kindle
Dynamical Biostatistical Models presents statistical models and methods for the analysis of longitudinal data. The book focuses on models for analyzing repeated measures of quantitative and qualitative variables and events history, including survival and multistate models. Most of the advanced methods, such as multistate and joint models, can be ap