Regression Methods in Biostatistics

Linear, Logistic, Survival, and Repeated Measures Models

Author: Eric Vittinghoff,David V. Glidden,Stephen C. Shiboski,Charles E. McCulloch

Publisher: Springer Science & Business Media

ISBN: 1461413532

Category: Medical

Page: 512

View: 9631

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This new book provides a unified, in-depth, readable introduction to the multipredictor regression methods most widely used in biostatistics: linear models for continuous outcomes, logistic models for binary outcomes, the Cox model for right-censored survival times, repeated-measures models for longitudinal and hierarchical outcomes, and generalized linear models for counts and other outcomes. Treating these topics together takes advantage of all they have in common. The authors point out the many-shared elements in the methods they present for selecting, estimating, checking, and interpreting each of these models. They also show that these regression methods deal with confounding, mediation, and interaction of causal effects in essentially the same way. The examples, analyzed using Stata, are drawn from the biomedical context but generalize to other areas of application. While a first course in statistics is assumed, a chapter reviewing basic statistical methods is included. Some advanced topics are covered but the presentation remains intuitive. A brief introduction to regression analysis of complex surveys and notes for further reading are provided.
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Analysis of Repeated Measures Data

Author: M. Ataharul Islam,Rafiqul I Chowdhury

Publisher: Springer

ISBN: 9811037949

Category: Business & Economics

Page: 250

View: 4964

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This book presents a broad range of statistical techniques to address emerging needs in the field of repeated measures. It also provides a comprehensive overview of extensions of generalized linear models for the bivariate exponential family of distributions, which represent a new development in analysing repeated measures data. The demand for statistical models for correlated outcomes has grown rapidly recently, mainly due to presence of two types of underlying associations: associations between outcomes, and associations between explanatory variables and outcomes. The book systematically addresses key problems arising in the modelling of repeated measures data, bearing in mind those factors that play a major role in estimating the underlying relationships between covariates and outcome variables for correlated outcome data. In addition, it presents new approaches to addressing current challenges in the field of repeated measures and models based on conditional and joint probabilities. Markov models of first and higher orders are used for conditional models in addition to conditional probabilities as a function of covariates. Similarly, joint models are developed using both marginal-conditional probabilities as well as joint probabilities as a function of covariates. In addition to generalized linear models for bivariate outcomes, it highlights extended semi-parametric models for continuous failure time data and their applications in order to include models for a broader range of outcome variables that researchers encounter in various fields. The book further discusses the problem of analysing repeated measures data for failure time in the competing risk framework, which is now taking on an increasingly important role in the field of survival analysis, reliability and actuarial science. Details on how to perform the analyses are included in each chapter and supplemented with newly developed R packages and functions along with SAS codes and macro/IML. It is a valuable resource for researchers, graduate students and other users of statistical techniques for analysing repeated measures data.
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Intuitive Biostatistics

A Nonmathematical Guide to Statistical Thinking

Author: Harvey Motulsky

Publisher: Oxford University Press, USA

ISBN: 0199730067

Category: Medical

Page: 447

View: 1884

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"Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists. New to this edition: Chapter 1 shows how our intuitions lead us to misinterpret data, thus explaining the need for statistical rigor. Chapter 11 explains the lognormal distribution, an essential topic omitted from many other statistics books. Chapter 21 contrasts testing for equivalence with testing for differences. Chapters 22, 23, and 40 explore the pervasive problem of multiple comparisons. Chapters 24 and 25 review testing for normality and outliers. Chapter 35 shows how statistical hypothesis testing can be understood as comparing the fits of alternative models. Chapters 37 and 38 provide a brief introduction to multiple, logistic, and proportional hazards regression. Chapter 46 reviews one example in great depth, reviewing numerous statistical concepts and identifying common mistakes. Chapter 47 includes 49 multi-part problems, with answers fully discussed in Chapter 48. New "Q and A" sections throughout the book review key concepts"--Provided by publisher.
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Applied Statistical Methods in Agriculture, Health and Life Sciences

Author: Bayo Lawal

Publisher: Springer

ISBN: 3319055550

Category: Medical

Page: 799

View: 5690

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This textbook teaches crucial statistical methods to answer research questions using a unique range of statistical software programs, including MINITAB and R. This textbook is developed for undergraduate students in agriculture, nursing, biology and biomedical research. Graduate students will also find it to be a useful way to refresh their statistics skills and to reference software options. The unique combination of examples is approached using MINITAB and R for their individual strengths. Subjects covered include among others data description, probability distributions, experimental design, regression analysis, randomized design and biological assay. Unlike other biostatistics textbooks, this text also includes outliers, influential observations in regression and an introduction to survival analysis. Material is taken from the author's extensive teaching and research in Africa, USA and the UK. Sample problems, references and electronic supplementary material accompany each chapter.
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Statistics with Applications to the Biological and Health Sciences

Author: M. Anthony Schork,Richard D. Remington

Publisher: Pearson College Division

ISBN: N.A

Category: Medical

Page: 478

View: 4734

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A book/disk text for a one- or two-semester course in basics of applied biostatistics. Learning features include summaries of formulas and terms, exercises, and statistical tables. This third edition reduces emphasis on methods of computation, and concentrates more on the rationale and utility of v
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McGraw-Hill Specialty Board Review Cardiology

Author: Ragavendra R. Baliga

Publisher: McGraw Hill Professional

ISBN: 0071614095

Category: Medical

Page: 1250

View: 4254

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An all-in-one review for the cardiology boards – complete with a CD-ROM with 600+ board-style questions McGraw-Hill Specialty Board Review: Cardiology is the ideal cardiology primer – whether you’re studying for board certification or seeking a thorough review of current thinking in cardiovascular medicine. You’ll find everything you need in one all-inclusive package: a CD-ROM with hundreds of board-style questions and thorough explanations; bulleted practical points at the beginning of each chapter; tables, charts, graphs, references and suggested reading; and more than 1000 illustrations – many in full color. Everything you need to pass the boards or keep abreast of this ever-changing field:“br/> Coverage of all specialty topics in general cardiology –- from prevention and imaging to heart failure Companion CD-ROM with 600+ questions in the exam style with detailed answer explanations Streamlined bulleted presentation and numerous tables and charts Suggested Reading or references at the end of each chapter Content that reflects mainstream thinking rather than a limited single-center perspective Content that spans all major areas of Cardiology: General Topics, Pulmonary, Preventive Cardiology, Coronary Artery Disease, Acute Coronary Syndrome, Intervention, Imaging, Heart Failure, Electrophysiology, Valvular Heart Disease, Congenital Heart Disease, Aorta and Vascular Diseases, Special Topics (Cardiac Tumors, HIV and Heart, Infective Endocarditis).
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Concise Biostatistical Principles & Concepts

Guidelines for Clinical and Biomedical Researchers

Author: Laurens Holmes Jr.

Publisher: AuthorHouse

ISBN: 1491843497

Category: Science

Page: 390

View: 8557

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Biostatistics deals with making sense of data. While statistical inference is essential in our application of the research findings to clinical decision-making regarding the care of our patients, statistical inference without clinical relevance or importance can be very misleading and even meaningless. This textbook has attempted to deemphasize p value in the interpretation of clinical and biomedical data by stressing the importance of confidence intervals, which allow for the quantification of evidence. For example, a large study due to a large sample size that minimizes variability may show a statistically significant difference while in reality the difference is too insignificant to warrant any clinical relevance. Covers these relevant topics in biostatistics: Design Process, Sampling & Reality in Statistical Modeling Basics of Biostatistical Reasoning & Inference Central Tendency Theorem & Measures of Dispersion Most commonly used & abused parametric test t test Most commonly used & abused non-parametric test chi squared statistic Sample size and power estimations Logistic/Binomial Regression Models Binary Outcomes Time-to-Event Data - Survival Analysis & Count Data Poisson Regression ANOVA, ANCOVA Mixed Effects Model (Fixed and Random), RANOVA,GEE Simple & Multiple Linear Regression Models Correlation Analysis (Pearson & Spearman Rank) Clinical & Statistical Significance p value as a function of sample size Clinical and biomedical researchers often ignore an important aspect of evidence discovery from their funded or unfunded projects. Since the attempt is to illustrate some sets of relationships from the data set, researchers often do not exercise substantial amount of time in assessing the reliability and validity of the data to be utilized in the analysis. However, the expected inference or the conclusion to be drawn is based on the analysis of the un-assessed data. Reality in statistical modeling of biomedical and clinical research data remains the focus of scientific evidence discovery, and this book. This text is written to highlight the importance of appropriate design prior to analysis by placing emphasis on subject selection and probability sample and the randomization process when applicable prior to the selection of the analytic tool. In addition, this book stresses the importance of biologic and clinical significance in the interpretation of study findings. The basis for statistical inference, implying the quantification of random error is random sample, which had been perpetually addressed in this book. When studies are conducted without a random sample, except when disease registries/databases or consecutive subjects are utilized, as often encountered in clinical and biomedical research, it is meaningless to report the findings with p value.
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Catalogs of Courses

Author: University of California, Berkeley

Publisher: N.A

ISBN: N.A

Category:

Page: N.A

View: 1571

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Includes general and summer catalogs issued between 1878/1879 and 1995/1997.
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