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The last 6 years has seen many advances in our knowledge of illnesses The DSM-IV-TRV spans the bridge between DSM- IVV and DSM-VV to ensur e that the most relevant new information since the DSM- IVV literature review in 1992 was incorporated and to enhance the educational value. Specifically, new information on associated features, including asso ciated laboratory and physical findings, has been added for many of th e disorders. Sections on prevalence, gender/age/culture, course, and familial pattern have also been revised to reflect recent research fin dings. More comprehensive differential diagnoses have been incorporat ed for many of the disorders..
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"Creswell's Research Design is an accessible and useful book that stimulates students through walk through experiences, use of exercises, and production of actual writing samples. It is a book that models the types of issues that best suit different approaches and allows students to understand when to use mixed methods. Furthermore, its focus on theory and paradigms is done in a way that helps students decode their meaning."

--MARTHA MONTERO-SIEBURTH, University of Massachusetts, Boston

"One of the most formidable challenges of research design is stating your purpose. Creswell's approach takes the guesswork out of the process."

--STEVE GUERRIERO, Organization & Management, Antioch New England Graduate School

The Second Edition of the bestselling Research Design: Qualitative, Quantitative, and Mixed Methods Approaches offers a unique comparison of three key approaches to inquiry. This comparison begins with preliminary consideration of knowledge claims for all three approaches, a review of the literature, and reflections about the importance of writing and ethics in scholarly inquiry. The book also addresses the key elements of the process of research: writing an introduction; stating a purpose for the study; identifying research questions and hypotheses; using theory; defining, delimiting and stating the significance of the study; and advancing methods and procedures for data collection and analysis.

Key Features:

• Provides a clear presentation of how to implement a mixed methods design in your proposal or plan as well as show how to implement qualitative and quantitative approaches
• Presents the ethical issues that may arise in quantitative, qualitative and mixed methods studies
• Offers extensive writing tips to help get your research plan started in the right direction
• Contains the latest developments in qualitative inquiry—including advocacy, participatory, and emancipatory approaches

This book is ideal for readers who seek assistance in designing a full research study or planning a proposal for a scholarly journal article, dissertation or thesis. The book is an invaluable reference on the basics of research design as well as an effective text for graduate courses in Research Methods, Research Design, and related topics. The book serves a broad audience of social and human scientists in fields of marketing, management, criminal justice, psychology, sociology, K-12 education, higher and post-secondary education, nursing, health sciences, urban studies, and family research.

 

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Brand new book, autographed by author..
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Getting started with SAS is easy with The Little SAS Book. This friendly, easy-to-read guide gently introduces you to the most commonly used features of SAS software plus a whole lot more! The book has been revised to include concepts of the Output Delivery System; the STYLE= option in the PRINT, REPORT, and TABULATE procedures; ODS HTML, RTF, PRINTER, and OUTPUT destinations; PROC REPORT; more on PROC TABULATE; exporting data; and the colon modifier for informats. You'll find clear and concise explanations of basic SAS concepts (such as DATA and PROC steps), inputting data, modifying and combining data sets, summarizing and presenting data, basic statistical procedures, and debugging SAS programs. Each topic is presented in a self-contained, two-page layout complete with examples and graphics. This format enables new users to get up and running quickly, while the examples allow you to type in the program and see it work!.
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Bring the miracle of Lean Six Sigma improvement out of manufacturing and into services

Much of the U.S. economy is now based on services rather than manufacturing Yet the majority of books on Six Sigma and Lean--today's major quality improvement initiatives--explain only how to implement these techniques in a manufacturing environment.

Lean Six Sigma for Services fills the need for a service-based approach, explaining how companies of all types can cost-effectively translate manufacturing-oriented Lean Six Sigma tools into the service delivery process.

Filled with case studies detailing dramatic service improvements in organizations from Lockheed Martin to Stanford University Hospital, this bottom-line book provides executives and managers with the knowledge they need to:

• Reduce service costs by 30 to 60 percent
• Improve service delivery time by 50 percent
• Expand capacity by 20 percent without adding staff

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Praise for previous editions:

"This book really is a life saver … If the mere thought of statistics gives you a headache, then this is the book for you." - Statistics student, UK

"I just wanted to say how much I value Julie Pallant's SPSS Survival Manual. It’s quite the best text in SPSS I’ve encountered and I recommend it to anyone who’s listening!" - Professor Carolyn Hicks, Birmingham University, UK

"… one of the most useful functional pieces of instruction I have seen. So, gold star and thanks." - Instructional designer, USA

"There are several SPSS manuals published and this one really does 'do what it says on the tin' ... Whether you are a beginner doing your BSc or struggling with your PhD research (or beyond!), I wholeheartedly recommend this book." - British Journal of Occupational Therapy, UK

Praise for the new edition:

"An excellent introduction to using SPSS for data analysis ... It provides a self-contained resource itself, with more than simply (detailed and clear) step-by-step descriptions of statistical procedures in SPSS. There is also a wealth of tips and advice, and for each statistical technique a brief, but consistently reliable, explanation is provided." - Associate Professor George Dunbar, Department of Psychology, University of Warwick, UK

In this fully revised edition of her bestselling text, Julie Pallant guides you through the entire research process, helping you choose the right data analysis technique for your project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting SPSS output and an example of how to present the results in a report.

For both beginners and experienced SPSS users in psychology, sociology, health sciences, medicine, education, business and related disciplines, the SPSS Survival Manual is an essential guide. Illustrated with screen grabs, examples of output and tips, it is supported by a website with sample data and guidelines on report writing.

In this third edition all chapters have been updated to accommodate changes to SPSS procedures, screens and output in version 15. A new flowchart is included for SPSS procedures, and factor analysis procedures have been streamlined. It also includes more examples and material on syntax. Additional data files are available on the book's supporting website..
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There has been a dramatic growth in the development and application of Bayesian inferential methods Some of this growth is due to the availability of powerful simulation-based algorithms to summarize posterior distributions. There has been also a growing interest in the use of the system R for statistical analyses. R's open source nature, free availability, and large number of contributor packages have made R the software of choice for many statisticians in education and industry.

Bayesian Computation with R introduces Bayesian modeling by the use of computation using the R language. The early chapters present the basic tenets of Bayesian thinking by use of familiar one and two-parameter inferential problems. Bayesian computational methods such as Laplace's method, rejection sampling, and the SIR algorithm are illustrated in the context of a random effects model. The construction and implementation of Markov Chain Monte Carlo (MCMC) methods is introduced. These simulation-based algorithms are implemented for a variety of Bayesian applications such as normal and binary response regression, hierarchical modeling, order-restricted inference, and robust modeling. Algorithms written in R are used to develop Bayesian tests and assess Bayesian models by use of the posterior predictive distribution. The use of R to interface with WinBUGS, a popular MCMC computing language, is described with several illustrative examples.

This book is a suitable companion book for an introductory course on Bayesian methods. Also the book is valuable to the statistical practitioner who wishes to learn more about the R language and Bayesian methodology. The LearnBayes package, written by the author and available from the CRAN website, contains all of the R functions described in the book.

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