Google Scholar Citations provide an estimate of the number of times published materials are referenced in subsequent works. The listing below of over 20 Harbor Branch library books represents books that have earned a minimum of 500 citations over their years in print.
Applied Regression Analysis by 
Continuous Univariate Distributions by 
The Delphi Technique in Nursing and Health Research by
The Delphi Technique in Nursing and Health Research is a practical guide to using the Delphi methodology for students and researchers in nursing and health. It adopts a logical step-by-step approach, introducing the researcher to the Delphi, outlining its development, analysing key characteristics and parameters for its successful use and exploring its applications in nursing and health. The book addresses issues of methodology, design, framing the research question, sampling, instrumentation, methodological rigour, reliability and validity, and methods of data analysis. The Delphi Technique in Nursing and Health Research enables the reader to be aware of the limitations of the technique and possible solutions, to design a Delphi questionnaire for each of the different rounds of a study, to consider different approaches to the technique in relation to a study, to analyse the data from each round of a Delphi study, and to understand the importance of feedback between rounds. Key Features A practical guide to facilitate use of the Delphi technique Provides the reader with the necessary information to participate in and conduct Delphi studies Examines different types of Delphi, including the e-Delphi, and modifications made to the technique Includes examples of real empirical investigations, brief case scenarios and key learning points for each chapter Explores the role of the Delphi researcher Explores ethical issues and issues of anonymity, use of experts and controlled feedback
Continuous multivariate distributions by 
Essentials of Nursing Research by
This eighth edition of Essentials of Nursing Research, written by AJN award-winning authors, along with its accompanying Study Guide for Essentials of Nursing Research, student learning ancillaries, and instructor teaching materials present a unique learning-teaching package that is designed to teach students how to read and critique research reports, and to appreciate the application of research findings to nursing practice. New to this edition: - New text organization with separate sections on quantitative and qualitative research offer greater continuity of ideas to better meet the needs of students and faculty. - New online chapter supplements for every chapter expand student's knowledge of research topics. - New chapter on mixed methods research, which involves the blending of qualitative and quantitative data in a single inquiry, responds to the surge of interest in this type of research - Increased emphasis on evidence-based practice (EBP) especially in the areas of asking well-worded questions for EBP and searching for such evidence guides the reader from theory to application. - Enhanced assistance for instructors with numerous suggestions on how to make learning about--and teaching--research methods more rewarding. -New interactive critiquing activity, available on thePoint website, brings the Critical Thinking Exercises from the textbook to an interactive tool. The new format makes it easy for students to respond to the series of targeted questions about the Research Examples. Responses can be printed or e-mailed directly to instructors for homework or testing.
Essentials of Research Design and Methodology by
Master the essential skills for designing and conducting asuccessful research project Essentials of Research Design and Methodology contains practicalinformation on how to design and conduct scientific research in thebehavioral and social sciences. This accessible guide covers basicto advanced concepts in a clear, concrete, and readablestyle. The text offers students and practitioners in the behavioralsciences and related disciplines important insights intoidentifying research topics, variables, and methodologicalapproaches. Data collection and assessment strategies,interpretation methods, and important ethical considerations alsoreceive significant coverage in this user-friendly guide.Essentials of Research Design and Methodology is the only availableresource to condense the wide-ranging topics of the field into aconcise, accessible format for handy and quick reference. As part of the Essentials of Behavioral Science series, this bookoffers a thorough review of the most relevant topics in researchdesign and methodology. Each concise chapter features numerouscallout boxes highlighting key concepts, bulleted points, andextensive illustrative material, as well as "Test Yourself"questions that help you gauge and reinforce your grasp of theinformation covered.
Introduction to Linear Regression Analysis by
A comprehensive and thoroughly up-to-date look at regression analysis-still the most widely used technique in statistics today As basic to statistics as the Pythagorean theorem is to geometry, regression analysis is a statistical technique for investigating and modeling the relationship between variables. With far-reaching applications in almost every field, regression analysis is used in engineering, the physical and chemical sciences, economics, management, life and biological sciences, and the social sciences. Clearly balancing theory with applications, Introduction to Linear Regression Analysis describes conventional uses of the technique, as well as less common ones, placing linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. Succeeding chapters include detailed coverage of: * Indicator variables, making the connection between regression and analysis-of-variance modelss * Variable selection and model-building techniques * The multicollinearity problem, including its sources, harmful effects, diagnostics, and remedial measures * Robust regression techniques, including M-estimators, Least Median of Squares, and S-estimation * Generalized linear models The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation. Topics not usually found in a linear regression textbook, such as nonlinear regression and generalized linear models, yet critical to engineering students and professionals, have also been included. The new critical role of the computer in regression analysis is reflected in the book's expanded discussion of regression diagnostics, where major analytical procedures now available in contemporary software packages, such as SAS, Minitab, and S-Plus, are detailed. The Appendix now includes ample background material on the theory of linear models underlying regression analysis. Data sets from the book, extensive problem solutions, and software hints are available on the ftp site. For other Wiley books by Doug Montgomery, visit our website at www.wiley.com/college/montgomery.
An Introduction to Probability Theory and Its Applications by
A complete guide to the theory and practical applications of probability theory An Introduction to Probability Theory and Its Applications uniquely blends a comprehensive overview of probability theory with the real-world application of that theory. Beginning with the background and very nature of probability theory, the book then proceeds through sample spaces, combinatorial analysis, fluctuations in coin tossing and random walks, the combination of events, types of distributions, Markov chains, stochastic processes, and more. The book's comprehensive approach provides a complete view of theory along with enlightening examples along the way.
Measurement in Nursing and Health Research by
Designated a Doody's Core Title This is a valuable resource for readers seeking basic to advanced information on measurement. It should be on the bookshelf of all researchers, and a requirement for graduate nursing students.Score: 100, 5 stars--Doody's Medical Reviews ...this book is a wonderful shelf reference for nurse researcher mentors and investigators who may need to explore content or use content to design, test, select, and evaluate instruments and methods used in measuring nurse concepts and outcomes."--Clinical Nurse Specialist This fourth edition presents everything nurses and health researchers need to know about designing, testing, selecting, and evaluating instruments and methods for measuring in nursing. Thoroughly updated, this fourth edition now contains only the latest, most cutting-edge measurement instruments that have direct applicability for nurses and health researchers in a variety of roles, including students, clinicians, educators, researchers, administrators, and consultants. Using clear and accessible language, the authors explain in detail, and illustrate by example, how to conduct sound measurement practices that have been adequately tested for reliability and validity. This edition is enriched with topics on the leading edge of nursing and health care research, such as measurement in the digital world, biomedical instrumentation, new clinical data collection methods, and methods for measuring quality of care. Key features: Provides new and emerging strategies for testing the validity of specific measures Discusses computer-based testing: the use of Internet research and data collection Investigates methods for measuring physiological variables using biomedical instrumentation Includes information on measurement practices in clinical research, focusing on clinical data collection methods, such as clinimetrics Identifies the challenges of measuring quality of care and how to address them
Nonparametric Statistical Methods by 
Nursing Research by
This graduate level nursing research textbook continues the expansion of coverage on qualitative research, including important issues for specific qualitative traditions such as grounded theory, phenomenology and ethnography. Developing solid evidence for practice will be emphasized throughout the text, and important evaluative concepts like reliability, validity, and trustworthiness will be introduced. Other new features include stronger international content (with an emphasis on Canadian and Australian research), inclusion of “tips” in boxes located in appropriate places throughout the chapters, and the use of summary bullet points. This edition will now offer a free Connection Website, connection.LWW.com/go/polit.
Practical Nonparametric Statistics by 
Qualitative Research in Nursing by
Qualitative Research in Nursing is a user-friendly text that systematically provides a sound foundation for understanding a wide range of qualitative research methodologies, including triangulation. It approaches nursing education, administration, and practice and gives step-by-step details to instruct students on how to implement each approach. Features include emphasis on ethical considerations and methodological triangulation, instrument development and software usage; critiquing guidelines and questions to ask when evaluating aspects of published research; and tables of published research that offer resources for further reading.
Qualitative Research Methods for the Social Sciences by
This book offers the most comprehensive and straightforward coverage of doing qualitative research on the market, now with a new chapter on Action Research. The author's central purpose remains a desire to instruct inexperienced researchers in ways of effectively collecting, organizing, and making sense of qualitative data, while stressing the importance of ethics in research and in taking the time to properly design and think through any research endeavor. After reading this book, fledgling researchers should be able to design, collect, and analyze data and then present their results to the scientific community.
Statistical Models by
This lively and engaging textbook provides the knowledge required to read empirical papers in the social and health sciences, as well as the techniques needed to build statistical models. The author explains the basic ideas of association and regression, and describes the current models that link these ideas to causality. He focuses on applications of linear models, including generalized least squares and two-stage least squares. The bootstrap is developed as a technique for estimating bias and computing standard errors. Careful attention is paid to the principles of statistical inference. There is background material on study design, bivariate regression, and matrix algebra. To develop technique, there are computer labs, with sample computer programs. The book's discussion is organized around published studies, as are the numerous exercises - many of which have answers included. Relevant papers reprinted at the back of the book are thoroughly appraised by the author.
Strategies for Theory Construction in Nursing by
Completely updated in a new 5th edition, this book details the advances that have been made in theory development and demonstrate the continued relevance of theory to nursing practice. Chapters discuss concepts, statement, and theory development with recently published examples of theory strategies, emphasizing concept analytical work. Introductory chapters clarify the relevance of theory to nursing practice, while concluding chapters contain a greater emphasis on how theories can be tested for validity and utility in practice. Features include: Recent theory development work being done by nurses; Emergent philosophical views that reflect increased diversity; International nursing theory development. Updated material through-out Preliminary Notes that engage the reader with a personal voice.
Theoretical Nursing by
Revised and updated for its Fifth Edition, Theoretical Nursing provides a comprehensive developmental and historical review of nursing theory. This text offers a contemporary analysis of the evolution of nursing and represents the degree to which many scholars view the focus and mission of nursing as a discipline through the development of its theoretical base. Chapters provide readers with different frameworks that shape the nature, the scope, and the mission of nursing care. Theoretical Nursing offers stimulating content that highlights the forces that are driving nursing care, education, research, and administration. The book presents practical perspectives that help the scholar to develop analytic skills and integrate knowledge into a coherent whole.
Understanding Nursing Research by
Learn how to evaluate and apply research with the #1 nursing research book! Understanding Nursing Research: Building an Evidence-Based Practice is known for its authoritative content, a time-tested step-by-step approach, and abundant use of research examples. With improved clarity and readability, the new edition strengthens its focus on evidence-based practice to better demonstrate how the steps of the research process relate to evidence-based nursing. Written by two of the leaders in the field of nursing research, Nancy Burns and Susan K. Grove, this full-color text offers unique insights into understanding, appraising, and applying published research to evidence-based practice. Authoritative content is written by two of the true pioneers in nursing research, who offer unique, first-hand insights into the field. Research examples provide practice in working with published studies, with many of the examples including Critical Appraisal and Implications for Practice sections. A clear, step-by-step organization introduces the research process and demonstrates how this systematic framework relates to evidence-based practice. An expanded emphasis on evidence-based practice helps you develop skills in studying and appraising published research, so you are prepared for your role in working with research evidence. Enhanced coverage of qualitative research allows prepares you to approach research questions and clinical questions with an unbiased view of the researcher's methodology. Two different appraisal processes are included: A traditional in-depth critical appraisal process prepares you for graduate-level work in research. A concise, practice-focused research appraisal process equips you for quick and accurate evaluation of the applicability of research findings to clinical practice. Updated research examples prepare you for evidence-based practice by using the physiologic conditions and hospitalized patients seen in clinicals.
Using Software in Qualitative Research by Some HBOI Library shelf items are also available in e-book format, such as those appearing below. Some editions may be found at other FAU Library locations. Check the library catalog to locate what is most relevant to your search.
Applied Regression Analysis by
An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts and applications, offers a complete, easily accessible introduction to the fundamentals of regression analysis. Assuming only a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear and nonlinear regression models, using small and large data sets, with pocket calculators or computers. This Third Edition features separate chapters on multicollinearity, generalized linear models, mixture ingredients, geometry of regression, robust regression, and resampling procedures. Extensive support materials include sets of carefully designed exercises with full or partial solutions and a series of true/false questions with answers. All data sets used in both the text and the exercises can be found on the companion disk at the back of the book. For analysts, researchers, and students in university, industrial, and government courses on regression, this text is an excellent introduction to the subject and an efficient means of learning how to use a valuable analytical tool. It will also prove an invaluable reference resource for applied scientists and statisticians.
Experimental Design and Data Analysis for Biologists by
An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.
Experimentation, Validation, and Uncertainty Analysis for Engineers by
Helps engineers and scientists assess and manage uncertainty at all stages of experimentation and validation of simulations Fully updated from its previous edition, Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes expanded coverage and new examples of applying the Monte Carlo Method (MCM) in performing uncertainty analyses. Presenting the current, internationally accepted methodology from ISO, ANSI, and ASME standards for propagating uncertainties using both the MCM and the Taylor Series Method (TSM), it provides a logical approach to experimentation and validation through the application of uncertainty analysis in the planning, design, construction, debugging, execution, data analysis, and reporting phases of experimental and validation programs. It also illustrates how to use a spreadsheet approach to apply the MCM and the TSM, based on the authors' experience in applying uncertainty analysis in complex, large-scale testing of real engineering systems. Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition includes examples throughout, contains end of chapter problems, and is accompanied by the authors' website www.uncertainty-analysis.com. Guides readers through all aspects of experimentation, validation, and uncertainty analysis Emphasizes the use of the Monte Carlo Method in performing uncertainty analysis Includes complete new examples throughout Features workable problems at the end of chapters Experimentation, Validation, and Uncertainty Analysis for Engineers, Fourth Edition is an ideal text and guide for researchers, engineers, and graduate and senior undergraduate students in engineering and science disciplines. Knowledge of the material in this Fourth Edition is a must for those involved in executing or managing experimental programs or validating models and simulations.
Handbook of mathematical functions with formulas, graphs, and mathematical tables by 
Introduction to Linear Regression Analysis by 
Solutions Manual to Accompany Introduction to Linear Regression Analysis by
As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Fifth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation.
Nonparametric Statistical Methods by
Praise for the Second Edition "This book should be an essential part of the personal library of every practicing statistician."--Technometrics Thoroughly revised and updated, the new edition of Nonparametric Statistical Methods includes additional modern topics and procedures, more practical data sets, and new problems from real-life situations. The book continues to emphasize the importance of nonparametric methods as a significant branch of modern statistics and equips readers with the conceptual and technical skills necessary to select and apply the appropriate procedures for any given situation. Written by leading statisticians, Nonparametric Statistical Methods, Third Edition provides readers with crucial nonparametric techniques in a variety of settings, emphasizing the assumptions underlying the methods. The book provides an extensive array of examples that clearly illustrate how to use nonparametric approaches for handling one- or two-sample location and dispersion problems, dichotomous data, and one-way and two-way layout problems. In addition, the Third Edition features: The use of the freely available R software to aid in computation and simulation, including many new R programs written explicitly for this new edition New chapters that address density estimation, wavelets, smoothing, ranked set sampling, and Bayesian nonparametrics Problems that illustrate examples from agricultural science, astronomy, biology, criminology, education, engineering, environmental science, geology, home economics, medicine, oceanography, physics, psychology, sociology, and space science Nonparametric Statistical Methods, Third Edition is an excellent reference for applied statisticians and practitioners who seek a review of nonparametric methods and their relevant applications. The book is also an ideal textbook for upper-undergraduate and first-year graduate courses in applied nonparametric statistics.
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