Book Description

Many biologists remain unfamiliar with statistical analysis and modelling, yet need to apply these techniques increasingly in their research.This volume describes how to analyze biological data, with commonly available software packages, without making errors which can invalidate results.Practical guidance is provided for planning the correct strategy for a variety of different statistical approaches and modelling problems and interpreting the results.Many examples of computer commands and output are given to illustrate the different analytical approaches. Biological Data Analysis: A Practical Approach has been designed specifically to allow researchers with only a minimal knowledge of statistics to understand a variety of statistical methods and apply them directly.The provision of data sets from several biological disciplines will make this book useful to all types of biologists. ... Read more

Book Description

Statistical analysis typically involves applying theoretically generated techniques to the description and interpretation of collected data. In this text, theory, application and interpretation are combined to present the entire biostatistical process for a series of elementary and intermediate analytic methods. The theoretical basis for each method is discussed with a minimum of mathematics and is applied to a research data example using a computer system called S-PLUS. This system produces concrete numerical results and increases one's understanding of the fundamental concepts and methodology of statistical analysis.

This text is not a computer manual, even though it makes extensive use of computer language to describe and illustrate applied statistical techniques. This makes the details of the statistical process readily accessible, providing insight into how and why a statistical method identifies the properties of sampled data. The first chapter gives a simple overview of the S-PLUS language. The subsequent chapters use this valuable statistical tool to present a variety of analytic approaches. Combining statistical logic, data and computer tools, the author explores such topics as random number generation, general linear models, estimation, analysis of tabular data, analysis of variance and survival analysis. The end result is a clear and complete explanation of the way statistical methods can help one gain an understanding of collected data.

Modern Applied Biostatistical Methods is unlike other statistical texts, which usually deal either with theory or with applications. It integrates the two elements into a single presentation of theoretical background, data, interpretation, graphics, and implementation. This all-around approach will be particularly helpful to students in various biostatistics and advanced epidemiology courses, and will interest all researchers involved in biomedical data analysis. ... Read more

Book Description

AIDS (autoimmune deficiency syndrome) is a devastating human disease caused by HIV, a human immunodeficiency virus, which may be transmitted by either sexual or other contacts in which body fluids are exchanged. Cases of AIDS have been reported in a majority of countries throughout the world, indicating that the HIV/AIDS epidemic is international in scope.

This book deals with the mathematical and statistical techniques underlying the models used to understand the population dynamics of not only HIV/AIDS but also other infectious diseases. Attention is given to the development strategies for the prevention and control of the international epidemic within the frameworks of the models. Two distinguishing features of the book are the incorporation of stochastic and deterministic formulations within a unifying conceptual framework and the discussion of issues related to the mathematical designs of models, which are necessary for the rigorous utilization of computer-intensive methods. The book will be of value to applied mathematicians, biomathematicians, biostatisticians, epidemiologists and other scientists interested in applying mathematics and computers to not only the HIV/AIDS epidemic but also other fields of epidemiology. ... Read more

Book Description

Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approaches that meld concepts, tools, and techniques from diverse areas, such as computer science, statistics, artificial intelligence, and financial engineering.Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques in areas such as market segmentation, customer profiling, image and speech analysis, and fraud detection. The chapter authors, who include such luminaries as Arnold Zellner, S. James Press, Stephen Fienberg, and Edward J. Wegman, present novel approaches and innovative models and relate their experiences in using data mining techniques in a wide range of applications. ... Read more

Book Description

This text enables biomedical researchers to use a number of advanced statistical methods that have proven valuable in medical research, and uses a statistical software package (Stata® ) to avoid mathematics beyond the high school level. Intended for people who have had an introductory course in biostatistics, the volume emphasizes the assumptions underlying each method, using exploratory techniques to determine the most appropriate method.It presents results in a way that will be readily understood by clinical colleagues. Numerous real examples from medical literature and graphical methods are used to illustrate these techniques. ... Read more

Reviews (4)

Very useful during statistics class
I used this book as the text for a biostatistics class that used STATA as the statistitical package. I found the organization, problems, and the STATA output the book provides, all very helpful. In addition, as I moved systematically through the book, the tips regarding using the STATA features were key to my learning many of the practical aspects of the STATA program.

Useful in conjuction with the manuals
As a non-statistician with some stat background, I find Dupont book a delightful book. It is packed with interesting and useful information. It starts at t-test and ends with GEE models, covering Cox model with time covariates along the way. But as the author noted, the book assumes some statistical knowledge and access to STATA maual. One minor note: While the book introduction asserts that it only assumes "high school mathematics" knowldege, the high school the author attended must be very different than the one I went to.

Buy this book if you like problem based learning
I have had the pleasure of using this book during a biostatistics level two course this year. The book is structured to assist in the course work in statistics using STATA. It is user friendly and gives mathematical explanations when appropriate but without losing the reader with too many equations. The book's approach uses problem based learning along with explanatory text which I found essential in learning to navigate STATA along with learning and understanding logistic regression, poisson regression etc. The best aspect of the book is the STATA output to assist with the problem solving. The book is a very good choice as an interactive tool for understanding advanced statistics using STATA.

Do not buy this book for learning STATA or methods
I decided to buy this book since this is a new book on teaching how to use STATA on advanced statistic methods. After I browsed this book, I do not think that this is a well-organized book. It does not show you how to use the latest and easiest STATA procedures to do analysis. Theory parts of statistic methods are hard to be read and even not as good as the remarks of STATA Reference. I am totally disappointed. ... Read more

Book Description

Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It focuses on providing a comprehensive treatment of marginal, conditional, and random effects models using, among others, likelihood, pseudo-likelihood, and generalized estimating equations methods. The authors motivate and illustrate all aspects of these models in a variety of real applications. They discuss several variations and extensions, including individual-level covariates and combined continuous and discrete outcomes. Flexible modelling with fractional and local polynomials, omnibus lack-of-fit tests, robustification against misspecification, exact, and bootstrap inferential procedures all receive extensive treatment. The applications discussed center primarily, but not exclusively, on developmental toxicity, which leads naturally to discussion of other methodologies, including risk assessment and dose-response modelling.Clearly written, Topics in Modelling of Clustered Data offers a practical, easily accessible survey of important modelling issues. Overview models give structure to a multitude of approaches, figures help readers visualize model characteristics, and a generous use of examples illustrates all aspects of the modelling process. ... Read more

Book Description

This casebook is designed for use in courses on epidemiology or occupational epidemiology. The chapters are based on actual studies and are written by the principal investigators. They are divided into four parts: cohort studies, case-control and proportionate mortality studies, cross-sectional studies, and surveillance and screening studies. A brief introduction to each part describes the study design, and a statistical appendix is included so that students can easily find the tools needed to answer analytical questions in the text. Questions in each chapter deal with study design, data collection, analysis, and interpretation. Complete answers are provided at the end of each chapter. Data sets accompany many of the chapters, and most of the analytical questions can be answered with a pocket calculator.

The studies presented in this lucid, well-organized text involve a broad range of disease outcomes, including spontaneous abortion, carpal tunnel syndrome, kidney dysfunction, cytogenetic changes, ischemic heart disease, dermatitis, chronic renal disease, and several types of cancer. The exposures of interest are equally diverse, including VDT use, repetitive hand-wrist motion, heavy metals, carbon monoxide, diesel exhaust, lead, vinyl chloride, pesticides, solvents, silica, and acid mists. These outcomes and exposures cover many of the current topics of interest in occupational health. ... Read more

Book Description

With continued progress in mapping and sequencing of the human genome, and increasing recognition of the role of genes in disease etiology, there is a need for a more sophisticated approach to the investigation of the causes of complex chronic diseases.This text integrates the principles, methods and approaches of epidemiology and genetics in the study of disease etiology.After a brief historical overview of genetics and epidemiology and their gradual rapprochement, the authors define the central theme of genetic epidemiology as the study of the role of genetic factors and their interaction with environmental factors in the occurrence of disease in populations.They describe fundamental research strategies of genetic epidemiology including population and family studies. Among the former are the study of the distribution of genetic traits and the role of nonspecific genetic indicators (such as inbreeding and admixture) in the occurrence of diseases.Among the latter are the analysis of familial aggregation of disease and its causes by epidemiologic methods as well as techniques of formal genetic analysis (variance components, segregation and linkage analysis).Finally, the authors discuss the increasing applications of genetic epidemiology in preventive medicine, public health surveillance, and the emerging ethical issues regarding use of genetic information in society. ... Read more

Reviews (2)

unique, comprehensive approach to genetic epidemiology
the authors present an epidemiologic approach to the study of genetic and environmental factors in health and disease. The book is comprehensive and lucid -- and captivatingly simple. I find myself going back to sections of the back even years after having read it the first time. One suggestion: the section on linkage analysis is, in my view, not easy to read and digest as the rest of the book. If you look for texts on linkage, other choices may serve you best. For everything else (on the epidemiologic approach to gene-environment interactions), I know of no better book. It should be integrated with a review paper or two on more recent techniques (TDT, case-triads, case-only studies) that have been developed after the publication of the book. This book is in my library to stay.

Difficult. Not a great stand alone textbook.
There are some useful nuggets for graduatre students, but this is a very difficult book to use as a primary textbook for learning methods. It is also somewhat out of date ... Read more

Book Description

Modern survival analysis and more general event history analysis may be effectively handled in the mathematical framework of counting processes, stochastic integration, martingale central limit theory and product integration. This book presents this theory, which has been the subject of an intense research activity during the past one-and-a- half decades. The exposition of the theory is integrated with careful presentation of many practical examples, almost exclusively from the authors' own experience, with detailed numerical and graphical illustrations. Statistical Models Based on Counting Processes may be viewed as a research monograph for mathematical statisticians and biostatisticians, although almost all methods are given in concrete detail to be used in practice by other mathematically oriented researchers studying event histories (demographers, econometricians, epidemiologists, actuarial mathematicians, reliabilty engineers and biologists). Much of the material has so far only been available in the journal literature (if at all), and so a wide variety of researchers will find this an invaluable survey of the subject."This book is a masterful account of the counting process approach...is certain to be the standard reference for the area, and should be on the bookshelf of anyone interested in event-history analysis." --International Statistical Institute Short Book Reviews"...this impressive reference, which contains a a wealth of powerful mathematics, practical examples, and analytic insights, as well as a complete integration of historical developments and recent advances in event history analysis." --Journal of the American Statistical Association ... Read more

Book Description

The Foundations of Epidemiology is an introductory level text intended for a broad range of courses in epidemiology, including those in medical schools, schools of public health, dental schools, schools of nursing, and other professional schools.Minimal familiarity with statistics is assumed in the book, although the text is not intended as a primary introduction to statistics; an appendix provides the necessary overview of statistics necessary to understand epidemiologic concepts, including sampling, significance testing, confidence intervals, correlation and linear regression, relative risks and attributable fractions, the life table, and Cohen's Kappa statistic.

Basic epidemiologic concepts, such as rates and ratios, age adjustment, incubation periods, investigation of an outbreak time-place-and person, agent-value, inter- and intra-observer variability, odds ratios, randomized trials, and cohort and case-control study designs are illustrated using examples from a variety of conditions, including asthma, food poisoning, coronary heart disease, measles, stroke, lung cancer, ovarian cancer, breast cancer, venous thrombosis, histoplasmosis, lyme disease, and AIDS.

The text consists of 13 chapters, each of which includes study problems and solutions.A discussion of the uses of epidemiology in clinical settings includes a guide to the critical review of medical and related literature. ... Read more

Book Description

Approaching computational statistics through its theoretical aspects can be daunting. Often intimidated or distracted by the theory, researchers and students can lose sight of the actual goals and applications of the subject. What they need are its key concepts, an understanding of its methods, experience with its implementation, and practice with computational software.Focusing on the computational aspects of statistics rather than the theoretical, Computational Statistics Handbook with MATLAB uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors integrate the use of MATLAB throughout the book, allowing readers to see the actual implementation of algorithms, but also include step-by-step procedures to allow implementation with any suitable software. The book concentrates on the simulation/Monte Carlo point of view, and contains algorithms for exploratory data analysis, modeling, Monte Carlo simulation, pattern recognition, bootstrap, classification, cross-validation methods, probability density estimation, random number generation, and other computational statistics methods.Emphasis on the practical aspects of statistics, details of the latest techniques, and real implementation experience make the Computational Statistics Handbook with MATLAB more than just the first book to use MATLAB to solve computational problems in statistics. It also forms an outstanding, introduction to statistics for anyone in the many disciplines that involve data analysis. ... Read more

Reviews (6)

Good Book for me...
There were a lot of negative comments for this book on Amazon so I sort of held off the purchase of this book. However, last week I ordered the book and quickly realised it is very useful. The book may lack detailed theory but excellent references are scattered throughout if you really want to follow it up. And the book is easy reading and well written with most statistical concepts defined before they are used.

The focus of this book primarily is to explain how to work on statistics using Matlab and it provides a taste of various areas with adequate explanations and code to get started. One advantage of this book is they do not define their own notation but use the notation which is currently in vogue in academia.

If you are starting out in Matlab, are not a statistician and do not have previous experience with other packages (like Splus or R) you should definetly think about getting a copy. If you are a Stats Guru you can just read the toolbox documentation. However note that these authors provide their additional stats toolbox FREE (which is also well written) on the website which contains most of Matlab statistical functions so you could save yourself some money on the Stats toolbox.

Disappointing
I think there would be a real interest in a book on "computational statistics" and related topics that showed details of analyses and algorithms using Matlab. This book is expensive and extremely disappointing.The explanations are sparse and very weak and the m.files are usually small add-ons to functions from the Stats Toolbox.

I think in any book on this topic there have to be detailed explanations of how methods work and what their limitations are.Otherwise the reader can find themselves in a lot of trouble very quickly. There is insufficient detail either for a student coming to the topics for the first time or for someone actually wanting to analyse data.

Other books that people might want to have a look at:
1)Statistical Pattern Recognition 2nd edition . Andrew Webb.This is not oriented to any particular language.Good introduction.
2)Netlab. Ian Nabney (this has excellent Matlab functions for neural networks)
3)Modern applied statistics with S 4th edition, Venables and Ripley. This uses a different language (but which will be relatively easy for Matlab users to learn), but learning S or R (free!) makes a huge number of tools available.
4)The recent data mining book by Hand et al. This offers clear and cogent explanations.It is good for someone who does not want overly mathematical descriptions.

I haven't looked properly at the recent Hastie,Friedman and Tibishirani book yet, but you can find reviews on the Amazon page for the book.

Not very useful
My major complain was that the authors, in general, did not present algorithms clearly. Limit selections of algorithms did not help either. As a result, you cannot use this book as a reference because it just does not contain enough material. You cannot learn much about computational statistics with this book becuase the statistic methods and algorithms are not adequately presented. you cannot even write codes for your own statistic analysis with the MATLAB examples shown in the book unless you have the Statistics Toolbox.
The only persons that might be benefit from this book are those who don't want to read the Statistics Toolbox manual on line. Given that the Mathworks no longer ship printed manuals, this book may be used a companion of the Statistics Toolbox.

sloppy writing
I ordered this book assuming to get something useful, but i got the impression while reading the book that it is like a collection of notes from other books, wrapped with some matlab code. More worrying to me was that the mathematics makes a sloppy impression. For me that means I cannot grab the book to lookup something and use the code without having to be concerned on the validity. The bottomline being I will not use it for applications and the book is a waste of money.

Instantaneous Classic!
As an independent student of probability and statistics this was a great find. You get a great overview of the useful algorithms of computational statistics. The chapter on Exploratory Data Analysis with its use of multidimensional graphing was very enlightening. It's wonderful that each topic is accompanied by source code (free on-line) that lets you see exactly how it's done. It's easy to tweak the code and explore your own data as you go along. You get just enough theory to understand the algorithm and lots of good common sense and rules-of-thumb on how to best apply it. Finally, the extensive bibliography and chapter-by-chapter annotations will point you straight to the best source for more in-depth study. ... Read more

Book Description

INTRODUCTORY APPLIED BIOSTATISTICS provides a solid and engaging background for students learning to apply and appropriately interpret statistical applications in the medical and public health fields. The many examples drawn directly from the authors' remarkable clinical experiences with applied biostatistics make this text relevant, practical, and interesting for students. This flexible textbook encourages students to master application techniques by hand before moving on to computer applications with SAS programming code and output for each technique covered in every chapter. The majority of the textbook addresses methods for statistical inference, including one- and two-sample tests for means and proportions, analysis of variance techniques, correlation and regression analysis.For each topic, the book addresses methodology, including assumptions, statistical formulas, and appropriate interpretation of results. ... Read more

Book Description

Emphasis on clustering of data of gene tissues
* Includes new research findings and activities in molecular biology
* Highlights the important general field of bioinformatics and genomics and discusses the impact of microarray analysis on both ... Read more

Book Description

Multivariable analysis is a challenging subject for clinicians, whether they are novice researchers or trained practitioners.Most basic biostatistics books do not cover multivariable analysis, while existing multivariable analysis books are dense with mathematical formulas. Multivariable Analysis:A Practical Guide for Clinicians steps aside from mathematics and offers conceptual explanations.Dr. Mitchell Katz follows a nonthreatening, question-and-answer approach to explain how to perform and interpret multivariable analyses.He begins by explaining why clinicians should do multivariable analyses and then guides the reader through topics such as how to choose which type of multivariable method to perform, how to deal with missing data, and how to validate multivariable models. The book is loaded with useful tips, tables, figures, and references. Examples from the medical literature demonstrate several real-world applications and uses of multivariable analysis. This book will prove to bean indispensable guide for medical students, residents, and practicing physicians. ... Read more

Reviews (5)

Poor organization: But Brief and Well Written
I used this book for a class last year. I found the organization quite horrible. There are 3 main multivariate models that he discusses in the book: Multiple regression, logistic regression and Cox proportional hazards. He ignores ANCOVA, ANOVA and multi-level frequency table (chi-square) methods.

Instead of writing about the 3 main multivariate models above individually he sporadically switches between all 3 models. The TOC is organized as a series of questions and answers. I would have preferred he wrote about each of the 3 topics separately.

Although finding the information you want is difficult, the book is written superbly. He makes it easy to understand difficult concepts such as interactions, model building, collinearity and testing of assumptions. You don't need a math background to understand this book. Aside from the organization of the contents, I loved this book! I would recommend for clinicians who are interested in learning about how multivariate models are created. If you review a lot of manuscripts in medical literature, this is a must read.

It' a real pleasure!
This is one of the best books I have ever read about biostatistics. It takes you further -from the usually well known table statistics to the model statistics using a step by step approach. Without covering the overall field, it tries to fortell readers' questions and answers them in the most explicit way. It's a book to understand what is going on around journals and makes your steps easier once you decide to try your way to dive in your numbers.

An easy understanding of multivariate analysis!
Straightforward approach to the concepts of multivariate analysis (MA) in medicine. If you don't know anything about MA and wanna understand it in a easy and fast way, this is the book. Katz also helps you to perform your own analysis. However, it's important to point out that a solid basis on statistical methods are needed for choosing the best method in a particular situation. The Cox model is not the solution for all problems!!! No strong math background is needed. This is a book of concepts and not of techniques. At least I can guarantee you'll understand the multivariate analysis published in NEJM and will find out about how common multivariate analyses are inappropriately used in medical journals. A big plus that every physician must read!

Finally,an user-friendly statistic book
I have to say I'm really impressed by this book. Its problem-based,user-friendly approach is a stand-out among all other statistic textbooks. The author did an excellent job in explaining the difficult concept of multivariable analysis using easy-to-read English and no jagons. Highly recommended for all.

An Excellent Primer on Multivariable Analysis
Biostatistics books are notorious for overwhelming the reader with dense terminology and advanced equations. Unfortunately, this type of book leaves those with a less advanced understanding of statistics scratching their heads. Mitchell Katz's book finally offers an accessible road map for the non-biostatistician on how to carry out multivariable analysis. While the target audience is clinicians, I would recommend it for anyone with an interest in multivariable analysis. Mitchell Katz has succeeded in assembling a concise, easy to understand, step-by-step guide to statistical analysis. For this rare accomplishment, I applaud the author. ... Read more

Book Description

Healthy People 2010 softcover contains the complete text, volumes 1 and 2, of the sentinel Healthy People report.Healthy People is a national health promotion and disease prevention initiative that brings together national, State, and local government agencies; nonprofit, voluntary, and professional organizations; businesses; communities; and individuals to improve the health of all Americans, eliminate disparities in health, and improve years and quality of healthy life. Healthy People 2010 builds on the goals and initiatives of Healthy People 2000. ... Read more

Book Description

This book contains the content of the ActivEpi CD-ROM pages plus additional exercises and an appendix on computer packages. ... Read more

Reviews (2)

ActivEpi Companion Textbook and CD Rom
The ActivEpi CD-Rom and Companion Text are a great combination. ActiveEpi is very quantitative - the depth of the coverage is beyond almost all typical intro epi textbooks. ActivEpi covers the basic material of measures of disease frequency and study designs. The Lessons on bias-related issues are very detailed and go into much more detail than found in almost any other epi text. The issues of interaction and confounding are covered in detail, as well as how to assess these in stratification and logistic regression. Also very in-depth discussion on matched case-control studies. There are a large number of quizzes and exercises. Highly recommended.

A First Edition Text in Need of Revision
The ActiveEpi Companion Text is a companion to the ActiveEpi CD-ROM. Although marketed as both a "general reference" and "self-contained" textbook, it is neither. Many epidemiologic concepts are discussed with insufficient depth and important shades of grey are not called to the reader's attention. The ActiveEpi Text also falls short as a companion for the CD. It contains some of the busiest and most unappealing graphics I've ever seen: 1). Black and white text with low resolution figures and diagrams in various shades of gray; 2). Excessive underlining, italicizing and bolding; 3). More than a half dozen fonts on most pages; and 4). Lines of text closely crammed together with numerous boxes of every size and shape on many pages. The text also has quite a few typos and grammatical errors. Just a few examples from the first chapter include "elements of each area respond to a single mouse clicks" (p. 3), "it would be worthwhile to review the them one more time" (p. 8), and "the Homerwork and Projects for each lesson" (p. 12). ... Read more