8/31/2011

Gerotranscendence: A Developmental Theory of Positive Aging Review

Gerotranscendence: A Developmental Theory of Positive Aging
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Just the best thing I have seen on understanding the developmental possibilities of old age.

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Given the 2006 GREAT GERONTOLOGY AWARD for outstanding contribution to gerontological research by the Swedish Gerontological Society

Received a VALUE GROUND AWARD from the journal Aldreomsorg (Old Age Care)
Expanding upon his earlier writings, Dr. Tornstam's latest book explores the need for new theories in gerontology and sets the stage for the development of his theory of gerotranscendence. This theory was developed to address what the author sees as a perpetual mismatch between present theories in social gerontology and existing empirical data.

The development towards gerotranscendence can involve some overlooked developmental changes that are related to increased life satisfaction, as self-described by individuals. The gerotranscendent individual typically experiences a redefinition of the Self and of relationships to others and a new understanding of fundamental existential questions:

The individual becomes less self-occupied and at the same time more selective in the choice of social and other activities.
There is an increased feeling of affinity with past generations and adecreased interest in superfluous social interaction.
The individual might also experience a decrease in interest inmaterial things and a greater need for solitary "meditation." Positive solitude becomes more important.
There is also often a feeling of cosmic communion with the spirit ofthe universe, and a redefinition of time, space, life and death.

Gerotranscendence does NOT imply any state of withdrawal or disengagement, as sometimes erroneously believed. It is not the old disengagement theory in new disguise. Rather, it is a theory that describes a developmental pattern beyond the old dualism of activity and disengagement.

The author supports his theory with insightful qualitative in-depth interviews with older persons and quantitative studies. In addition, Tornstam illustrates the practical implications of the theory of gerotranscendence for professionals working with older adults in care settings. A useful Appendix contains suggestions of how to facilitate personal development toward gerotranscendence.
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8/30/2011

Essentials of Psychological Testing Review

Essentials of Psychological Testing
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This book should be required for every School Psychology student. It has all the basics for testing. I definitely see myself using it as a reference throughout the rest of my graduate career and my career in the field.

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An excellent primer on the key concepts of psychometrics Essentials of Psychological Testing surveys the basic principles of psychometrics, supplies the information needed to understand and evaluate tests, and introduces readers to the major contemporary reference works in the field.It is the only book to provide such a thorough and up-to-date overview of psychometrics in an engaging, accessible format. As part of the Essentials of Behavioral Science series, this book offers an overview of the most relevant psychometric concepts and techniques that provides the foundation necessary for knowledgeable, informed practice. Each concise chapter features numerous callout boxes highlighting key concepts, bulleted points, and extensive illustrative material, as well as "Test Yourself" questions that help to gauge and reinforce readers’ grasp of the information covered.Starting with a basic introduction to psychological tests, their historical development, and their uses, Essentials of Psychological Testing also covers the statistical procedures most frequently used in testing, the frames of reference for score interpretation, reliability, validity, and test item considerations, as well as guidelines for test selection, administration, scoring, and reporting test results. Whether as an orientation for those new to the field, a refresher for those already acquainted with it, or as a reference for seasoned clinicians, Essentials of Psychological Testing is an invaluable resource on the fundamentals of this evolving area of practice.

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8/29/2011

Statistics for Health Care Professionals: Working With Excel (Public Health/Epidemiology and Biostatistics) Review

Statistics for Health Care Professionals: Working With Excel (Public Health/Epidemiology and Biostatistics)
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This book is helpful and easy to use.
I am taking a class so that also helps, but it really breaks things down so that you can understand.

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Statistics for Health Care Professionals: Working with Excel (second edition) is written in a clear, easily followed style keyed to the powerful statistical tool, Microsoft Excel 2007. It introduces the use of statistics applicable to health administration, health policy, public health, health information management, and other professions, emphasizing the logic of probability and statistical analysis in all areas. Coverage includes data acquisition, data display, basics of probability, data distributions, confidence limits and hypothesis testing, statistical tests for categorical data, tests for related and unrelated data, analysis of variance, simple linear regression, multiple regression, and analysis with a dichotomous categorical dependent variable. A glossary and section-by-section review questions round out this uniquely comprehensive and accessible text.

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8/28/2011

Whistle-Blowing in Organizations (Lea's Organization and Management Series) Review

Whistle-Blowing in Organizations (Lea's Organization and Management Series)
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interesting book with lots of factual knowledge. it must be understood that it is a specific book written about whistleblowing with research on whistleblowing therefore for research book is great as over night reading not great.

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Thisis a research-based book on whistle-blowing in organizations. The three noted authors describe studies on this important topic and the implications of the research and theory for organizational behavior, managerial practice, and public policy. In the past few years there have been critical developments, including corporate scandals, which have called public attention to whistle-blowing and have led to the first comprehensive federal legislation to protect private sector whistle-blowers (the Sarbanes-Oxley Act). This bookis the first to integrate these new developments in an analytic and empirically grounded approach to whistle-blowing in organizations.

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8/27/2011

Saving Children from a Life of Crime: Early Risk Factors and Effective Interventions (Studies in Crime and Public Policy) Review

Saving Children from a Life of Crime: Early Risk Factors and Effective Interventions (Studies in Crime and Public Policy)
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This sociology study documents exactly how many much more effective ways America can keep children from committing crimes than by prosecuting them as adults and locking them up forever. Children are not just little adults; emotional intelligence must be learned, and it can be taught.

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After decades of rigorous study in the United States and across the Western world, a great deal is known about the early risk factors for offending. High impulsiveness, low attainment, criminal parents, parental conflict, and growing up in a deprived, high-crime neighborhood are among the most important factors. There is also a growing body of high quality scientific evidence on the effectiveness of early prevention programs designed to prevent children from embarking on a life of crime. Drawing on the latest evidence, Saving Children from a Life of Crime is the first book to assess the early causes of offending and what works best to prevent it. Preschool intellectual enrichment, child skills training, parent management training, and home visiting programs are among the most effective early prevention programs. Criminologists David Farrington and Brandon Welsh also outline a policy strategy--early prevention--that uses this current research knowledge and brings into sharper focus what America's national crime fighting priority ought to be. At a time when unacceptable crime levels in America, rising criminal justice costs, and a punitive crime policy have spurred a growing interest in the early prevention of delinquency, Farrington and Welsh here lay the groundwork for change with a comprehensive national prevention strategy to save children from a life of crime.

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8/26/2011

Statistics for Spatial Data (Wiley Series in Probability and Statistics) Review

Statistics for Spatial Data (Wiley Series in Probability and Statistics)
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This is a wonderful source of information on methods for analyzing spatial data. It is still reasonably current for this rapidly developing area in statistics. You won't find some of the latest research on the joint modeling of space and time. But I expect that Cressie is working on a book that will cover it. It is an encyclopedia of references. The author covers the gamut of techniques. This explains why the book is so lengthy. I think that if he plans a revision he will be more selective and only cover those methods that have proved to be the most promising. Here you can finally learn what kriging is and even see how the bootstrap can be applied to spatial data.
Michael Stein's book is also very good and specializes in kriging. This book may look pricy at $138 but given the size of the book, the content and current textbook prices, this is a good buy.

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The first practical look at spatial statistics for the scientist and engineer. Designed for the scientific and engineering professional eager to exploit its enormous potential, Statistics for Spatial Data is a primer to the theory as well as the nuts-and-bolts of this influential technique. Focusing on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, and reveals how spatial statistical models can be used to solve a host of problems in science and engineering. Revised to reflect state-of-the-art developments, this edition also features many detailed examples, numerous illustrations, and over 1,000 references. The first fully comprehensive introduction, Statistics for Spatial Data is an essential guide for professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology. "This excellent book, which presents the most important branches of modern spatial statistics in an exemplary manner, will become a basic reference book and will popularize many methods which have been used until now only by small circles of specialists." -Mathematical Reviews "The majority of geoscientists should make sure they have access to this volume, while for those who are actively involved in applying statistical methods to data (of all sorts) this book should be in their personal libraries. As a compendium of statistical procedures to use to analyze data, this volume will surely provide a good solid framework for some time to come." -Geophysics

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8/25/2011

Statistical Design and Analysis of Experiments, with Applications to Engineering and Science Review

Statistical Design and Analysis of Experiments, with Applications to Engineering and Science
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Mason, Gunst and Hess have done a great deal of consulting in industry which has provided them with an understanding of the design and analysis of linear and nonlinear models. In fact, I have had some direct experience with Bob Mason from Southwest Research Institute. When I was working at a medical device company owned by St. Jude Medical Inc., Southwest Research Institute had been contracted to analyze data from one of our animal experiments for defibrillation thresholds. As the new statistician in the company I needed to get acquainted with their work. The book illustrates many designs using real world problems. The first 5 chapters (88 pages) cover elementary statistical concepts and methods. The next 6 chapters (145 pages) cover designs. Most standard designs are covered including full factorials, balanced incomplete blocks, latin squares, fractional factorials and nested and crossover designs. There is also a chapter on response surface designs including rotatable designs, central composite designs and Box-Behnken designs. The rest of the book, some 368 pages, deals with statistical analysis of data from designed experiments. It makes a very good reference source.
The only disadvantage of it is that there have been many advances in the design of experiments since 1989 when the book was published. The topic of robust parameter design is not covered because much of the development occurred after 1989. Hints of the topic and mention of the Taguchi approach appear only on pages 108-110. To learn much more about the recent developments in the design of experiments see Hamada and Wu (2000) "Experiments". My review of Hamada and Wu can be found on Amazon.

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Emphasizes the strategy of experimentation, data analysis, and the interpretation of experimental results.* Features numerous examples using actual engineering and scientific studies.* Presents statistics as an integral component of experimentation from the planning stage to the presentation of the conclusions.* Deep and concentrated experimental design coverage, with equivalent but separate emphasis on the analysis of data from the various designs.* Topics can be implemented by practitioners and do not require a high level of training in statistics.* New edition includes new and updated material and computer output.

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8/24/2011

Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling Review

Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling
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Snijders and Bosker's Multilevel Analysis is mathematically demanding but more readable than Raudenbush and Bryk's Hierarchical Linear Models. Snijders and Bosker's text would be much more useful for the less-experienced reader if it contained a directory identifying essential material. As is often the case with books of this kind, it is difficult to distinguish between really important topics, those crucial to understanding multilevel models, and ancillary topics which can be treated as non-essential, at least for the first pass through this dense and difficult material.
It would also help if the authors located multilevel modeling within a statistical context likely to contain material that readers already understand. As it is, multilevel analysis is treated as a separate and new topic, and is readily accessible only to those with generalized mathematical maturity.
The authors do, however, cover a broad range of pertinent material. Thus, while it is not a good choice for beginners looking for a self-instructional tool, the statistically sophisticated reader will find it to be an excellent reference. While just as difficult to understand as the rest of the book, Snijders and Bosker's develop some really informative and interesting examples of three-level models.
This text has been in print for a decade, and is still widely used. I've found that as I become more familiar with multilevel modeling, the book becomes more valuable.

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The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines.

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8/23/2011

Computer Architecture: A Quantitative Approach, 3rd Edition Review

Computer Architecture: A Quantitative Approach, 3rd Edition
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First, this is certainly not an introductory text on Computer Architectures. The authors assume that people reading it have already had an introductory class or some experience. Simply put, the book is not intended to explain how cache memory works, but to present a thourough quantitative analysis to show why and when one implementation works better than another, and what improvements have been devised recently to speed this or this other measurement.
Of course, the best choice for this book would be to have it preceeded by "Computer Organization: the HW/SW interface" (aka CO-HSI), by the same authors, since it would help to better comprehend the MIPS64 and the low-level design behind it, since CO-HSI develop an older version of the MIPS itself.
This is for sure one of the most informative books I've ever encountered both as a student and as a SW engineer. It contains an overwhelming quantity of data, tips, warnings, tecniques so that the over 1100 pages seem incredibly dense. And don't be fooled the book is "only so little": there are other seven online appendixes that can be downloaded, that will add up to more than 250 pages to the book.
As experience teaches, however, quantity does not always mean quality. Yet, it seems this doesn't apply to this book, because the quality of its content is highly informative and interesting for those involved with true CA designs.
Since the first chapter it's clear that target of the book is not a survery of CAs, but a guide through the bunch of considerations and problems a design of a new CA must cope with today. I mean today because much of the data collected and presented is binded to (and updated to) the current edition and its realease date. So covered CAs for this 3ed will feature IA-64 or Sony Playstation II among the others. Nonetheless, it would be misleading to think that next year the book will become useless. Most of the considerations the authors develop and present are quite long lasting (the usage patterns of ISAs, e.g., have incurred little change since the second edition, six years ago).
This edition presents noticeable changes, even if there's no doubt the core is that of CA-AQA 2ed. To mention a few, the first chapter is of course almost totally new since it's the most time-bounded of the book. The elder chapter four (Advanced Pipelining and Instruction Level Parallellism) has been expanded into two chapters, one dealing with Hardware approaches and one with Software approaches (and both with hybrid ones). This goes into great benefit for the reader since it seems we never get enough details on modern CAs and their complexity otherwise.
However, changes has been done even in the way of reductions, and that's especially true for the elder chapter three (Pipelining). It was a full 100 pages chapter, featuring an astonishing treatment of the topic, that has been fundamental in my class of CA II. In the 3ed edition, this chapter has been moved to a shorter appendix at the end, and I think this appendix can't compare with its predecessor (even if some of the "cut" topics have been then spread through chapters 3-4 in the 3ed).
About the exposition of the topics, the authors have built a solid way to make things clear for students and not, beginners and not on quantitative analysis. The book is full of figures, graph, citation and feature a wide bibliography at the end of the book and a reasoned set of references at the end of each chapter.
The only difficulties reading this book will arise only because of the complexity of the topics, who themselves require a fair amount of attention, not because of the language which keeps always clear and straightforward.
This said, I think the book is a fully deserved 5 stars one, with no concurrents on its kind, scope and utility. That's probabily why it has been worlwide used since its first edition.

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This best-selling title, considered for over a decade to be essential reading for every serious student and practitioner of computer design, has been updated throughout to address the most important trends facing computer designers today.In this edition, the authors bring their trademark method of quantitative analysis not only to high performance desktop machine design, but also to the design of embedded and server systems.They have illustrated their principles with designs from all three of these domains, including examples from consumer electronics, multimedia and web technologies, and high performance computing.
The book retains its highly rated features: Fallacies and Pitfalls, which share the hard-won lessons of real designers; Historical Perspectives, which provide a deeper look at computer design history; Putting it all Together, which present a design example that illustrates the principles of the chapter; Worked Examples, which challenge the reader to apply the concepts, theories and methods in smaller scale problems; and Cross-Cutting Issues, which show how the ideas covered in one chapter interact with those presented in others.In addition, a new feature, Another View, presents brief design examples in one of the three domains other than the one chosen for Putting It All Together.
The authors present a new organization of the material as well, reducing the overlap with their other text, Computer Organization and Design: A Hardware/Software Approach 2/e, and offering more in-depth treatment of advanced topics in multithreading, instruction level parallelism, VLIW architectures, memory hierarchies, storage devices and network technologies.
Also new to this edition, is the adoption of the MIPS 64 as the instruction set architecture. In addition to several online appendixes, two new appendixes will be printed in the book:one contains a complete review of the basic concepts of pipelining,the other provides solutions a selection of the exercises.Both will be invaluable to the student or professional learning on her own or in the classroom.
Hennessy and Patterson continue to focus on fundamental techniquesfor designing real machines and for maximizing their cost/performance. * Presents state-of-the-art design examples including:* IA-64 architecture and its first implementation, the Itanium * Pipeline designs for Pentium III and Pentium IV * The cluster that runs the Google search engine * EMC storage systems and their performance* Sony Playstation 2* Infiniband, a new storage area and system area network* SunFire 6800multiprocessor server and its processor the UltraSPARC III* Trimedia TM32 media processor and the Transmeta Crusoe processor* Examines quantitative performance analysis in the commercial server market and the embedded market, as well as the traditional desktop market.Updates all the examples and figures with the most recent benchmarks, such as SPEC 2000.* Expands coverage ofinstruction sets to include descriptions of digital signal processors, media processors, and multimedia extensions to desktop processors.* Analyzes capacity, cost,and performance of disks over two decades.Surveys the role of clusters in scientific computing and commercial computing.* Presents a survey, taxonomy, and the benchmarks of errors and failures in computer systems.* Presents detailed descriptions of the design of storage systems and of clusters.* Surveys memory hierarchies in modern microprocessors and the key parameters of modern disks.* Presents aglossary of networking terms.

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8/22/2011

Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS Review

Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS
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I am so happy purchased this book. Finally, I have this book.The handbook really assist me to analyse my multivariate data. Really guide me how write good finding report. Every PhD student should have this book. Make your data presentable in analytical and critical finding. Easy to understand. The handbook will make you expert in univariate and multivariate data analysis if we always practice the exercises. Interpretation with SPSS really assist me to produce good report. I bring this handbook every where I go...Thank you Dr Ho. I hope one day we will meet...

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Many statistics texts tend to focus more on the theory and mathematics underlying statistical tests than on their applications and interpretation. This can leave readers with little understanding of how to apply statistical tests or how to interpret their findings. While the SPSS statistical software has done much to alleviate the frustrations of social science professionals and students who must analyze data, they still face daunting challenges in selecting the proper tests, executing the tests, and interpreting the test results.With emphasis firmly on such practical matters, this handbook sets forth clear guidelines for performing specific statistical tests with SPSS and interpreting the output. The author clearly explains the purpose of each test and the research designs for which they are relevant, demonstrates the execution of the tests, and explains how to interpret the results obtained. The presentation covers not only the point-and-click Windowsä method of using SPSS, but also the syntax method, which provides users with the power and flexibility to deal with complex experimental designs. All chapters include the full SPSS output of the test being addressed and the step-by-step interpretation of the results. All of the data sets used in the examples along with the SPSS code are freely available for download at www.crcpress.com.Armed with the knowledge, tools, and experience this handbook provides, social scientists, both student and professional, can maximize the utility of SPSS, choose the right statistical tests with confidence, and more accurately and appropriately interpret their results.

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8/21/2011

Generalized Linear Models, Second Edition (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) Review

Generalized Linear Models, Second Edition (Chapman and Hall/CRC Monographs on Statistics and Applied Probability)
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This is an important book. It is a mature, deep introduction to generalized linear models.
General linear models extend multiple linear models to include cases in which the distribution of the dependent variable is part of the exponential family and the expected value of the dependent variable is a function of the linear predictor. Besides the normal (Gaussian) distribution, the binomial distribution, the Poisson distribution and the Gamma distribution, are just some of the exponential family members most frequently encountered in the scientific literature. Using appropriate functions to join the dependent variable to the linear predictor many classic models of applied statistics are included in the broad frame of generalized linear models: "logistic regression", log-linear models, Cox's proportional hazards models are just some of them.
Further extensions to the "base" family of generalized linear models, such as those based on the use of quasi-likelihood functions, and models in which both the expected value and the dispersion are function of a linear predictor, are well presented in the book.
Examples, and exercises, introduce many non-banal, useful, designs.
There are some minor drawbacks. Some more advanced topics might have been introduced more smoothly (i.e. conditional likelihood). Some other topics are better understood when you are already familiar with the specific object of study (i.e. Cox's proportional hazards models as a generalized linear model). The book does not provide software examples, nor is it related with any specific statistical package. However, the maturity of the reader to whom the book is addressed should be so high that translating the majority of the examples presented in the book in the "language" of a familiar statistical package should not be a problem.

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The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and other applications.The authors focus on examining the way a response variable depends on a combination of explanatory variables, treatment, and classification variables. They give particular emphasis to the important case where the dependence occurs through some unknown, linear combination of the explanatory variables.The Second Edition includes topics added to the core of the first edition, including conditional and marginal likelihood methods, estimating equations, and models for dispersion effects and components of dispersion. The discussion of other topics-log-linear and related models, log odds-ratio regression models, multinomial response models, inverse linear and related models, quasi-likelihood functions, and model checking-was expanded and incorporates significant revisions.Comprehension of the material requires simply a knowledge of matrix theory and the basic ideas of probability theory, but for the most part, the book is self-contained. Therefore, with its worked examples, plentiful exercises, and topics of direct use to researchers in many disciplines, Generalized Linear Models serves as ideal text, self-study guide, and reference.

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8/20/2011

An Introduction to Medical Statistics (Oxford Medical Publications) Review

An Introduction to Medical Statistics (Oxford Medical Publications)
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This is the second edition of an excellent introductory text for medical students similar to Doug Altman's. Bland covers the basics: designing clinical trials and epidemiological studies, data collection, summarizing data, basic probability, standard errors and confidence intervals along with tests of significance (both parametric and nonparametric). Various types of regression methods are covered and this edition adds Cox proportional hazards models and meta-analysis. Many exercises and examples are taken from Bland's 20 years of experience as a medical statistician. It is noteworthy for dealing with sample size issues in Chapter 18. Mortality statistics and life tables are covered in Chapter 16.
The book is not quite as advanced as Altman's.

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St. George's Hospital Medical School, London, UK. Textbook, for medical students, nurses, clinicians, and medical researchers, covers statistical work required for a course in medicine and for the exams of most Royal Colleges. Includes design of clinical trials and epidemiological studies, data collection, and summarizing and presenting data. Softcover.

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8/19/2011

Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition Review

Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition
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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.

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It’s been over a decade since the first edition of Measurement Error in Nonlinear Models splashed onto the scene, and research in the field has certainly not cooled in the interim. In fact, quite the opposite has occurred. As a result, Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition has been revamped and extensively updated to offer the most comprehensive and up-to-date survey of measurement error models currently available.
What’s new in the Second Edition?
· Greatly expanded discussion and applications of Bayesian computation via Markov Chain Monte Carlo techniques
· A new chapter on longitudinal data and mixed models
· A thoroughly revised chapter on nonparametric regression and density estimation
· A totally new chapter on semiparametric regression
· Survival analysis expanded into its own separate chapter
· Completely rewritten chapter on score functions
· Many more examples and illustrative graphs
· Unique data sets compiled and made available online
In addition, the authors expanded the background material in Appendix A and integrated the technical material from chapter appendices into a new Appendix B for convenient navigation. Regardless of your field, if you’re looking for the most extensive discussion and review of measurement error models, then Measurement Error in Nonlinear Models: A Modern Perspective, Second Edition is your ideal source.

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8/18/2011

The Gender Gap in College: Maximizing the Developmental Potential of Women and Men (Jossey-Bass Higher and Adult Education) Review

The Gender Gap in College: Maximizing the Developmental Potential of Women and Men (Jossey-Bass Higher and Adult Education)
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Women have earned more college degrees than men since 1982, yet women trail their male counterparts on many important indicators, such as academic self confidence, emotional health, and participation in athletics. Sax carefully documents these and other noteworthy trends using a rich source of data on college freshmen. She also carefully explores the impact of the college experience on young men and women. Sax makes every effort to make this excellent research accessible to the general public, but also provides enough detail to be informative to educators, college advisors, and scholars interested in education and gender. This book deserves of a wide audience for those interested in the experiences of women college students and those interested in understanding how the world is changing. For the complete version of this review, see the journal Gender & Society.

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Drawing on data from a sample of approximately 17,000 male and female students that represent 200 institutions, The Gender Gap in College examines the impact of college experiences, peer groups, and faculty on a comprehensive array of student outcomes. Author Linda Sax’s approach is unique because she directly examines the interaction between gender and a variety of college experiences, a major inquiry which addresses the fundamental "individualization” question: do women and men respond differently to a given educational experience? The areas covered in the book include academic achievement, self-concept, life goals, career development, physical and emotional health, political and social attitudes, and satisfaction with college.


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8/17/2011

A First Course in Stochastic Processes, Second Edition Review

A First Course in Stochastic Processes, Second Edition
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A remarkable well organised work. Every chapter contains all needed definitions and formulas, deep discussions of their meanings, proofs, and examples, all extraordinarily well blended. Also every chapter has two set of problems. The 'elementary problems' require applying the material covered. The 'problems' require to prove results, they provide an excellent ground to develop this skill. Some times the classic format proof-theorem is used, but usually the ideas flow: starting with a problem, introducing necessary definitions and finding a solution eventually a theorem is stated as a natural consequence.
The writing style is similar to the immortal 'Introduction to Probability Theory' and its Applications' by Feller, with a similar mixture of rigorous mathematics and probabilistic intuition. Though 'A First Course...' only reviews the basics, it has some common topics with Feller's and covers more advanced topics.
The style of the book is the perfect opposite of 'Introduction to probability Models' by Sheldon Ross, which is written in a much more flamboyant style, full of surprises and amazement, and requires the constant use of pencil and paper to follow the developments. These two sources can be combined to master the subject, despite the fact that students often find Ross's magnificent work too hard to follow. (Of course, some will say that it is a bad book, and that the professor can't teach...)
Even though 'A First Course...' is rarely used as a textbook (bad marketing?) after taking courses on multivariable calculus and basic probability, an undergraduate student is ready to read this book. Measure theory is barely used, and it is a surprise to see how far can one go using only probabilistic intuition. The book is also well suited to doctoral courses.
The consecutive chapters on Martingales and Brownian Motion are unparalleled, a unique collection of basic examples is used to illustrate results on Stopping Times and Convergence. Also, Measure Theory is introduced at this point in a very appealing manner. These concepts are then used to obtain classical results on Brownian Motion and other topics. Students interested in Stochastic Calculus (not covered in this book) and its many application in Finances, Engineering, Operations Research and Computer Science can acquire solid foundations here.
The chapter on Stationary Processes is also very special, it provides solid foundations for Econometrics and Time Series and it is often quoted in research papers.
In short: an excellent book to acquire solid foundations on Stochastic Processes, the only source I know for a simple and systematic introduction of certain topics.

Click Here to see more reviews about: A First Course in Stochastic Processes, Second Edition

The purpose, level, and style of this new edition conform to the tenets set forth in the original preface. The authors continue with their tack of developingsimultaneously theory and applications, intertwined so that they refurbish and elucidate each other.The authors have made three main kinds of changes. First, they have enlarged on the topics treated in the first edition. Second, they have added many exercises and problems at the end of each chapter. Third, and most important, they have supplied, in new chapters, broad introductory discussions of several classes of stochastic processes not dealt with in the first edition, notably martingales, renewal and fluctuation phenomena associated with random sums, stationary stochastic processes, and diffusion theory.

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8/16/2011

Forecasting Economic Time Series Review

Forecasting Economic Time Series
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This is a unique text that treats economic time series forecasting with emphasis on the recent advances in econometric theory such as cointegration as well as other practical strategies such as combination forecasts. Usual text books do not have the breadth of coverage this one attempts, successfully, to achieve. In short, this one text replaces many books and papers on one's shelf.

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David Hendry is one of the world's leading econometricians, and in this major new work he and Michael Clements provide an extended formal analysis of economic forecasting with econometric models: their analysis builds in many of the features of the real world that are often overlooked in traditional, textbook analyses of forecasting. Consequently, Clements and Hendry are able to suggest ways in which existing forecasting practices can be improved, as well as providing a rationale for some of the habitual practices of forecasters that have hitherto lacked a scientific foundation.

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8/15/2011

Introducing Anova and Ancova: A GLM Approach (Introducing Statistical Methods series) Review

Introducing Anova and Ancova: A GLM Approach (Introducing Statistical Methods series)
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This book's main features to me are concise, clear writing, while balancing an in-depth treatment of ANOVA and ANCOVA from a linear model perspective. While it was not the easiest read (I am a doctoral student as I'm writing this), I have not found any sections that leave me confused. If you are looking for an explanation of ANOVA that is tightly written and does not contain a lot of extra background information, you will likely find this book very useful.

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Traditional approaches to ANOVA and ANCOVA are now being replaced by a General Linear Modeling (GLM) approach. This book begins with a brief history of the separate development of ANOVA and regression analyses and demonstrates how both analysis forms are subsumed by the General Linear Model. A simple single independent factor ANOVA is analysed first in conventional terms and then again in GLM terms to illustrate the two approaches.The text then goes on to cover the main designs, both independent and related ANOVA and ANCOVA, single and multi-factor designs.The conventional statistical assumptions underlying ANOVA and ANCOVA are detailed and given expression in GLM terms. Alternatives to traditional ANCOVA are also presented when circumstances in which certain assumptions have not been met. The book also covers other important issues in the use of these approaches such as power analysis, optimal experimental designs, normality violations and robust methods, error rate and multiple comparison procedures and the role of omnibus F-tests.

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