Reviews (4)

Extremely Board Specific
I first encountered this book when it was called "Biostatistics for the Boards" when I took the course from Dr. Glaser when he was teaching at the American University of the Caribbean School of Medicine in 1990. Dr. Glaser was an exceptionally good and popular teacher and the book reflects his "no-nonsense" style. At first I thought it was a "dumbed down" statistics book as I had taken a full year of stats in college and my previous books had been huge and heavy textbooks. However, I soon found that the reason Dr. Glaser's book was so brief was that he concentrates only on the type of concepts and questions you will find on the USMLE step 1. The chapters are short and it is easy to review each one many times to firmly plant the info into long term memory. I had no problems at all with the stats on the USMLE. This book presents exactly what you need to answer all the questions on the USMLE without having you waste a lot of time studying things you will never use.

The best source for USMLE
Are you one of those people that are scared of Biostatistics? Fear no more!! This book is for you. It explains everything in a very smart and simple way. Plenty of examples and tests help you to master the subject. If you study this book well, you will "understand" biostatistics and you don't have to memorize nonsense informations. two thumbs up!

SIMPLY GREAT
ACTUALLY GIVES A HIGHER YIELD IN MARKS-AMUST HAVE

Statistics in a Nutshell
This dandy little book shares the keys of understanding college biostatistics with you. It's what you need to know to pass exams, boards and the like. It provides clear instruction on the essentials of descriptive and inferential statistics, hypothesis testing, correlational techniques, research methods, and statistics in epidemiology. For those who struggle with beginning and intermediate statistics classes, it's a jewel. ... Read more

Book Description

Group sequential methods answer the needs of clinical trial monitoring committees who must assess the data available at an interim analysis. These interim results may provide grounds for terminating the study-effectively reducing costs-or may benefit the general patient population by allowing early dissemination of its findings. Group sequential methods provide a means to balance the ethical and financial advantages of stopping a study early against the risk of an incorrect conclusion.Group Sequential Methods with Applications to Clinical Trials describes group sequential stopping rules designed to reduce average study length and control Type I and II error probabilities. The authors present one-sided and two-sided tests, introduce several families of group sequential tests, and explain how to choose the most appropriate test and interim analysis schedule. Their topics include placebo-controlled randomized trials, bio-equivalence testing, crossover and longitudinal studies, and linear and generalized linear models.Research in group sequential analysis has progressed rapidly over the past 20 years. Group Sequential Methods with Applications to Clinical Trials surveys and extends current methods for planning and conducting interim analyses. It provides straightforward descriptions of group sequential hypothesis tests in a form suited for direct application to a wide variety of clinical trials. Medical statisticians engaged in any investigations planned with interim analyses will find this book a useful and important tool. ... Read more

Reviews (1)

clear coverage for practicing biostatisticians
Advances in the theory of repeated significance testing in the 1980s and 1990s has made sequential methods practical by identifying stopping rules for data collected sequentially but in groups. This material is now used to plan interim analyses and both safety and efficacy group sequential trials for clinical trials. This text provides for the first time thorough coverage of these advances with suitable references to the literature.

It should be on the bookshelf of any biostatistician who conducts clinical trials for pharmaceutical or medical device companies. ... Read more

Book Description

This versatile textbook allows students and teachers to fashion an instructional package that meets diverse learning needs. It provides a wide-ranging look at basic and advanced biostatistical concepts and methods in a format calibrated to individual interests and levels of proficiency. Each topic presentation features introductory comments, real-life examples, a step-by-step outline of the statistical procedure under discussion, an explanation of applications, and numerous practice exercises. Advanced material-which may be included in coursework at the discretion of the instructor-has been noted throughout the text with asterisks, and notes at the end of each chapter extend and enrich the primary material. Early chapters discuss the design of medical studies, descriptive statistics, and introductory ideas of probability theory and statistical inference. Later chapters explore more advanced statistical methods and illustrate important current uses of biostatistics. Statistical methods discussed include
* Robustness and nonparametric statistics
* Analysis of variance and covariance
* Multiple comparisons
* Discrimination and classification
* Principal component analysis and factor analysis
* Survival analysis (including life tables, product-limit estimates, and Cox proportional hazards regression)
* Sample sizes for observational studies
With more than 390 practice exercises, clear illustrations and graphics, and more than 130 examples, Biostatistics provides a complete detailed seminar, which encourages steady, incremental growth while acting as a catalyst for creative analysis. ... Read more

Reviews (2)

From an M.D.'s perspective taking a Masters Degree in Stats
This was a terrible book. To say that it is user unfriendly is an understatement. It is wordy and too long, furthermore, it doesn't teach you what you need to know. It is difficult to reference things (for example, try looking up sensitivity in the index!) and the writing is very tangential. This is not a good book if you are just starting out. I would not receommend it.

nice intermediate level text in biostatistics
The authors write well and cover most of the important topics very thoroughly. They motivate the subject very well with a number of important and "real world" examples in the first chapter.

A unique feature is its detailed coverage of sample size determination in a number of contexts.

The book was published in 1993 which is not recent enough to cover advances in meta analysis, resampling, Bayesian Hierarchical Models (with Markov Chain Monte Carlo Methods) and frailty models. At least bootstrap methods and meta analyses are mentioned in the book.

Noteworthy are the full chapters on multiple comparison problems and discriminant analysis. This is an excellent reference book for biostatisticians. ... Read more

Book Description

This exceptional resource provides a well-grounded foundationfor the statistics portion of nursing research courses. The thirdedition continues to emphasize the reading, analysis and writing up ofresearch results, with insight offered on the how to of the process.Special focus is placed on the application of those concepts presentedin the text. A computer disk, included with the text, contains datasets that students can use to learn various statistical methods. Newhot topics include: Power Analysis, Effect Size, MultivariateInformation, and Data Hygiene. ... Read more

Reviews (3)

Statistical Methods for Health Care Research
A very well-written and helpful statistics book. It was required reading for a course in Quantitative Nursing Research last semester. Overall, the concepts such as t-tests, correlation and regression were explained in relatively simple terms. Examples with answers were found at the end of each chapter and the book came with a data disk. This was the most user-friendly statistics book that I have used so far!

Great book
I had a chance to review this book. I think the authors can make us much better understand, particularly one who is about to learn the concept of statistics. You can apply this book with the SPSS program in order to interpret the results. Anyway, I still like the calculation parts which are removed in this edition (3rd) compared with the last one. I think they can help someone, who is very interested in statistics, to understand better before go ahead to use the computer. It's a great book for the beginner.

A very user friendly approach to understanding statistics.
An excellent beginning reference book for anyone in need of understanding or interpreting univariate and multivariate statistics. Geared toward health care research, with many examples. A data set is provided with the book for students to use with different analyses. Reading audience is upper division undergraduate or graduate student. ... Read more

Book Description

One of the most challenging issues for clinical trial investigators, sponsors, and regulatory officials is the interpretation of experimental results that are composed of the results of multiple statistical analyses. These analyses may include the effect of therapy on multiple endpoints, the assessment of a subgroup analysis, and the evaluation of a dose-response relationship in complex mixtures.Multiple Analyses in Clinical Trials: Fundamentals for Clinical Investigators is an essentially nonmathematical discussion of the problems posed by the execution of multiple analyses in clinical trials. It concentrates on the rationale for the analyses, the difficulties posed by their interpretation, easily understood solutions, and useful problem sets. This text will help clinical investigators understand multiple analysis procedures and the key issues when designing their own work or reviewing the research of others. This book is written for advanced medical students, clinical investigators at all levels, research groups within the pharmaceutical industry, regulators at the local, state, and federal level, and biostatisticians. Only a basic background in health care and introductory statistics is required. Dr. Lemuel A. Moyé, M.D., Ph.D. is a physician and Professor of Biometry at the University of Texas School of Public Health. He has been Co-Principal Investigator of two multinational clinical trials examining the role of innovative therapy in post myocardial infarction survival (SAVE) and the use of cholesterol reducing agents in post myocardial infarction survival in patients with normal cholesterol levels (CARE). He has authored over one hundred articles in journals such as the Journal of the American Medical Association, the New England Journal of Medicine, Statistics in Medicine, and Controlled Clinical Trials. ... Read more

Book Description

This is a new paperback edition of the well received text Spatial Epidemiology: Methods and Applications. It is an easy to read, clear and concise exploration of the field of geographical variations in diseases. Especially with respect to variations in environmental exposures at the small-area scale this book gives an authoriative account of current practice and developments.The recent and rapid expansion of the field looks set to continue in line with growing public, governmental and media concern about environmental and health issues, and the scientific need to understand and explain the effects of environmental pollutants on health. Of interest to epidemiologists, public health pratitioners, statistcians, geographers, environmental scientists and others concerned with understanding the geographical distribution of disease and the effects of environmental exposures on human health.It will be a valuable source for undergraduate and postgraduate courses in epidemiology, medicial geography, biostatistics, environmental health and environmental science as well as a useful source of reference for health policy makers, health economists, regulators and others in the field of environmental health. ... Read more

Reviews (1)

Great New Spatial Methods Book for Epidemiology
"Spatial Epidemiology" mixes practical application with theory to provide a critical review of methods, challenges, issues, strengths, and limitations of spatial analysis in epidemiology. Subsections of the book progress from types of data, to statistical methods, to disease mapping and clustering, then end with exposures and links to health. Each subsection includes at least one chapter presenting spatial analytical theory, one chapter providing an overview of spatial analytical methods, one chapter reviewing a particular spatial analytical method in depth, a chapter applying a method, and one specialty chapter. Authors have included equations, comprehensive examples from both chronic and infectious diseases, and extensive references to other chapters and other works for each method presented. Earlier chapters provide a thorough background discussion of data issues that will be particularily useful to novices in the field. Statistical chapters assume intermediate or more advanced experience with spatial analysis, however, provide references to background and seminal works that will allow novices to the field to optimize their learning experience. There are several chapters devoted to cluster analysis, Bayesian analysis, and modeling which are particularily useful.

Overall, this is a very useful book for researchers at any level of experience with spatial analysis. Although technical terms are used liberally, the overall text is easy to read, clear and concise, serving well as both a teaching text and a reference book.

Other useful features:

List of abbreviations - very helpful for acronyms; Color maps; Comprehensive index; References - each chapter provides references to other works that provide more detail or background on the method under discussion ... Read more

Book Description

McMaster Univ., Hamilton, Canada. Pocket guide on understanding statistics, for anyone who must occasionally interpret the results section of a research article in scientific journals. Not intended as a textbook; light, often humorous writing style. Includes CD-ROM containing complete text and illustrations in fully searchable PDF files. Softcover. ... Read more

Reviews (4)

In a class of its own!
This book is the only statistics book of its type. For each section covering a specific statistical method (from simple methods to those you may not even cover in your PhD training), a concise 2-5 page summary is presented. The goal is not to enable the reader to calculate any of these statistics, but to understand conceptually what each statistic means. This is where it can fill in information other statistics texts never get to. A student (or researcher!) who can churn out factorial ANOVA results, but doesn't truly understand what they mean can turn to this book for clarity. It's simple (for statistics), it's short, it's clear, and you have to love a book that is dedicated "To the many people who have made this book both possible and necessary -- authors of other statistics books"!

The best
I've spent years looking for a book on statistics that is lucid for professionals who need to use statistical methods but who don't want to get a Ph.D. in math to be able to undertand them.

This book is the best. No incomprehensible Greek formulas. No tortured prose. And yet it's not just a mere introduction of what a mode is. It includes some advanced statistical methods and gives you all you need to know to understand what they do and how and when you would use them. It is long enough to describe each method sufficiently, including pitfalls and things to watch out for. Yet the book is short enough that reading it and undertanding the whole thing is possible in a modest length of time.

You can stop searching now. This is the book.

Don't fear the p-value!
This really is a fun book - yes FUN - I'd even say it's a bathroom book about statistics. It's very conceptual, not at all driven by formulas - and makes many statistical concepts crystal clear. A great book to pick up for the PHD or the stats phobic - -

Excellent resource for the statistically challenged!
If you are an analytically impaired and statistically challenged math phobe who needs to understand and use statistical methods, this is an excellent resource. The authors explanations are relevant and easy to understand. Highly recommended for those who need to get a grip on the numbers in research! ... Read more

Book Description

In Unbiased Steriology, the authors present a practical guide to making unbiased 3D measurements using microscopy. Stereology is the statistical inference of geometric parameters from spatially sampled information; it is considered unbiased whent he test probes are positioned in an appropriately random manner. Now that unbiased stereology is required for nerve-cell counts in neurotoxicology by the FDA and by many journals before the acceptance of an article or study, this book is essential reading. It includes only those stereological techniques that have been tried and tested by actual application. Although these techniques are essentially mathematical--unbiased stereology is a quantitative rather than qualitative approach to microscopy-the authors do not immerse the reader in complex theories. Instead, they provide simple heuristic explanations and references to the original proof, illustrating the theory with analogies draw from everyday experience. Exercises-provided at the end of each chapter, complete with detailed worked answers-have been developed by the authors or donated by other expert stereologists to give practical experience using the techniques. Specific topis covered include: random sampling and random geometry; the estimation of feature volume, surface, length, number and mean particle size; as well as statistics for stereologists. ... Read more

Reviews (1)

Extremely useful for all interested in true quantification
This is an excellent book for all those interested in true quantification of tissue elements. Here, methods are outlined, amply illustrated and put forward in the form of exercises making it a pleasure even for the novice reader to get an understanding of what stereology is and what it is for. Now, the day seems near when researchers report their results on quantitative tissue features based on stereological estimation procedures. Highly recommended for serious morphologists. ... Read more

Book Description

Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately.With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments examines the consequences and Bayesian remedies in those cases where the explanatory variable cannot be measured with precision.The author explores both measurement error in continuous variables and misclassification in discrete variables, and shows how Bayesian methods might be used to allow for mismeasurement. A broad range of topics, from basic research to more complex concepts such as "wrong-model" fitting, make this a useful research work for practitioners, students and researchers in biostatistics and epidemiology." ... Read more

Book Description

Millennium Pharmaceuticals, Inc., Cambridge, MA. Text provides formulas and procedures for determining the appropriate sample size for testing equality. Presents various statistical procedures, current regulatory requirements, methodology for design and analysis, and recent developments in clinical research. ... Read more

Book Description

Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling. Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material.Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research. ... Read more

Book Description

Providing a comprehensive picture of the design, conduct, analysis, and interpretation of non-experimental studies of both infectious and non-infectious diseases, the Second Edition of this widely used text has been thoroughly updated to take into account the numerous developments in epidemiology over the past decade. Since the first edition was published in 1986, additional sources of data have become available through the increasing use of computerized records for health-related purposes. Also, a better understanding of the uses and limitations of certain epidemiologic concepts has been gained. Modifications of traditional study designs, including nested case-control studies and case-cohort studies, are now more frequently employed. Biological markers of exposure, disease susceptibility, and disease itself are used in many studies and methods of statistical analysis have been further developed. All of these developments have been considered in writing the Second Edition.

The authors cover the full scope of observational studies, describing in detail cohort studies, case-control studies, cross-sectional studies, and epidemic investigation. The use of statistical procedures is described in easy-to-understand terms. Sample size estimation, sampling, measurement, and measurement error are fully discussed. Each chapter in the second edition has been updated and several chapters have been expanded. Chapter 3, which summarizes sources of data on disease occurrence, includes several additional sources of data. Chapter 5, which describes modifications of traditional study designs, now contains nested case-control and case-cohort studies. Chapter 15, on other types of measurement, has been expanded to include sections on measurement in epidemiologic studies of the elderly and on biological markers since these have become major areas of epidemiologic research in recent years. Much of the material in Chapters 6, 7, and 9 on the analysis of data from epidemiologic studies is also new to this edition.

Perhaps the greatest challenge for the authors in writing this Second Edition was to make some of the modern, frequently used methods of statistical analysis understandable to readers with a limited mathematical or statistical background. Although this book is intended for readers who have had introductory courses in epidemiology and biostatistics, even readers who do not fully comprehend the theory behind some of the techniques should understand the rationale for their use and be able to interpret results when they appear on a computer printout or in the literature. The Second Edition of this widely used text will serve as a practical resource for students and practitioners of epidemiology, public health and biostatistics. ... Read more

Reviews (1)

Good reference
I think this book,Methods in Observational Epidemiology, might be very good reference to many scientists, especially biostatistist or epidemiologists. ... Read more

Book Description

Over the last twenty years there has been a dramatic upsurge in the application of meta-analysis to medical research. This has mainly been due to greater emphasis on evidence-based medicine and the need for reliable summaries of the vast and expanding volume of clinical research. At the same time there have been great strides in the development and refinement of the associated statistical methodology. This book describes the planning, conduct and reporting of a meta-analysis as applied to a series of randomized controlled clinical trials.
* The various approaches are presented within a general unified framework.
* Meta-analysis techniques are described in detail, from their theoretical development through to practical implementation.
* Each topic discussed is supported by detailed worked examples.
* A comparison of fixed and random effects approaches is included, as well as a discussion of Bayesian methods and cumulative meta-analysis.
* Fully documented programs using standard statistical procedures in SAS are available on the Web.
Ideally suited for practising statisticians and statistically-minded medical professionals, the book will also be of use to graduate students of medical statistics. The book is a self-contained and comprehensive account of the subject and an essential purchase for anyone involved in clinical trials. ... Read more

Book Description

McGill University, Montreal, Canada. New edition of a practical text on the clinical use of statistics in medicine, for physicians and medical students without formal statistics education. Emphasizes explaining the purpose of statistical methods rather than the performance of calculations. ... Read more

Reviews (1)

Medical Uses of Statistics
I've been writing an overview of bio-statistics and have been immersed in a stack of statistics books and this one is my favorite, from the perspective of a non-statistician. Chapters are well organized and the material is covered thoroughly without bogging down in formulas. Medical professionals will find this to be an excellent resource for understanding the types of statistical methods used and reported in the well known medical journals. ... Read more

Book Description

Multilevel modelling facilitates the analysis of hierarchical data where observations may be nested within higher levels of classification. In health care research, for example, a study may be undertaken to determine the variability of patient outcomes where these also vary by hospital or health care region. Inference can then be made on the efficacy of health care practices. This book provides the reader with the analytical techniques required to study such data sets.
* First book to focus on multilevel modelling for health and medical research
* Covers the majority of analytical techniques required by health care professionals
* Unifies the literature on multilevel modelling for medical and health researchers
* Each contribution comes from a specialist in that area

Guiding the reader through various stages, from a basic introduction through to methodological extensions and generalised linear models, this test will show how various kinds of data can be analysed in a multilevel framework. Important statistical concepts, such as sampling and outliers, are covered specifically for multilevel data. Repeated measures, outliers, institutional performance, and spatial analysis, which have great relevance to health and medical research, are all examined for multilevel models.

The book is aimed at health care professionals and public health researchers interested in the application of statistics, and will also be of interest to postgraduate students studying medical statistics.

Wiley Series in Probability and Statistics ... Read more

Book Description

Good statistical design of experimental and analytical methods is a fundamental component of successful research. The set of tools that has evolved to implement these processes of design and analysis is called Biostatistics. Using these tools blindly or by rote is a recipe for failure.The Biostatistics Cookbook is intended for research scientists who want to understand why they do a particular test or analysis as well as how to do it. It is meant as an interpreter as well as a guide, helping the researcher to illuminate and communicate his or her results as accurately, concisely, and universally as possible. ... Read more

Book Description

Complex multivariate problems are frequently encountered in many scientific disciplines and it can be very difficult to obtain meaningful results. Permutation and nonparametric combination methods provide flexible solutions to complex problems by reducing the problem down to a set of simpler sub-problems. The author presents a novel but well tested approach using real examples taken from biomedical research. Statistical analyses are performed in a nonparametric setting, so that no assumptions need be made about the underlying distribution and the dependence relations between variables.

· Provides a clear exposition of the use of multivariate permutation testing, with emphasis on the use of nonparametric combination methodology.
· Growing area of research with many practical applications, notably in biostatistics.
· Numerous case studies and examples help to illustrate the theory.
· Provides solutions to multi-aspect problems, to problems with missing data, analysis of factorial designs and repeated measures.
· Explains the analysis of categorical, ordered categorical, binary, continuous, and mixed variables in both an experimental and an observational context.
· NPC-Test© software (demo copy), SAS macros, S-Plus code and datasets are available on the Web at
http://www.stat.unipd.it/~pesarin/
For researchers and practitioners in a number of scientific disciplines, particularly biostatistics, the vast collection of techniques, examples and case studies will be an invaluable resource. Graduate students of applied statistics and nonparametric methods will find the book provides an accessible introduction to multivariate permutation testing. ... Read more

Reviews (1)

The must book for a mastery of the theory of testing hypothe
The new Lehmann for the 20th century, this text presents the essential theorems of testing hypotheses while providing many original solutions for long standing problems including exact tests for two-way designs. ... Read more

Book Description

This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors.The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems.The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem.Measurement error occurs in many fields, such as biometry, epidemiology and economics.In particular, the book contains a large number of epidemiological examples.An outline of strategies for handling progressively more difficult problems is also provided. ... Read more

Reviews (1)

excellent coverage of special nonlinear models
Ray Carroll and David Ruppert are well known research statisticians who have published many joint articles on regression, weighted regression and transformation and they have also written an excellent book together on this research topic. Stefanski has recently published several papers on measurement error models with Carroll. Here they have teamed up to write a statistics text on a unique topic. Measurement error models are common and practical when dealing with covariates that have measurement error. Least squares estimation in linear regression is based on the assumption that the predictor variables are measured without error. There are many articles and an excellent text by Fuller "Measurement Error Models", published by Wiley in 1988 that deals with the linear case. Also look at a section in Chapter 5 of Miller's "Beyond ANOVA, Basics of Applied Statistics" that refers to the problem as the error in variables problem. For the nonlinear case this is the first treatment. Well written and well documented, this text provides an up-to-date account of the theory and methods and provides real applications (e.g. the Framingham Heart Study). This is a great reference as are many of the other monographs in this series by Chapman and Hall/CRC Press. Includes bootstrap approaches in the chapter on fitting methods and models. ... Read more