Clinical Statistics: Introducing Clinical Trials, Survival Analysis, and Longitudinal Data Analysis Reviews

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Clinical Statistics: Introducing Clinical Trials, Survival Analysis, and Longitudinal Data Analysis provides the mathematic background necessary for students preparing for a career as a statistician in the biomedical field. The manual explains the steps a clinical statistician must take in clinical trials from protocol writing to subject randomization, to data monitoring, and on to writing a final report to the FDA. All of the necessary fundamentals of statistical analysis: survival and longitudinal data analysis are included. SAS procedures are explained with simple examples and the mathematics behind these SAS procedures are covered in detail with the statistical software program SAS which is implemented throughout the text. Complete codes are given for every example found in the text. The exercises featured throughout the guide are both theoretical and applied making it appropriate for those moving on to different clinical settings. Students will find Clinical Statistics to be a handy lab reference for coursework and in their future careers.

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Building an up-to-date understanding of the methodologies that can be used to shape public health policies, Epidemiology: Study Design and Data Analysis, Second Edition encompasses the study of epidemiology from the observation of associations between risk factors and disease to the use of practical, data-supported analyses. It presents study designs commonly used for a wide range of purposes, and covers the spectrum of statistical principles and analytical tools used in epidemiological research, such as techniques used in report writing, descriptive analyses, statistical models and synthesis of evidence.

New Material in This Edition Includes:

Systematic evaluation

Meta-analysis

Regression dilution

Case-cohort studies

Case-crossover studies

Pooled logistic regression

Companion Web site containing data sets for examples and exercises, SAS and Stata code for examples, a sample size calculator, and a SAS floating absolute risk macro

The second edition of a popular textbook, this book emphasizes quantitative and design aspects of epidemiological research. The author favors the use of basic mathematics and practical methods over complicated mathematical proofs, making this an ideal textbook that is comprehensive yet accessible to graduate students in epidemiology, statistics, public health studies, and/or medical research.

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Using in-depth qualitative interviews, authors Herbert J. Rubin and Irene S. Rubin have researched topics ranging from community redevelopment programs to the politics of budgeting and been energized by the depth, thoroughness, and credibility of what was revealed. They describe in-depth qualitative interviewing from beginning to end, from its underlying philosophy and assumptions to project design, analysis and write up.

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This accessible introduction to data analysis focuses on the interpretation of statistical results, in particular those which come from nonexperimental social research. It will provide social science researchers with the tools necessary to select and evaluate statistical tests appropriate for their research question.

Using a consistent data-set throughout the book to illustrate the various analytic techniques, Michael Lewis-Beck covers topics such as univariate statistics, measures of association, the statistical significance of the relationship between two variables, simple regression in which the dependent variable is influenced by a single independent variable, and multiple regression.

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Bernard Rosner's FUNDAMENTALS OF BIOSTATISTICS is a practical introduction to the methods, techniques, and computation of statistics with human subjects. It prepares students for their future courses and careers by introducing the statistical methods most often used in medical literature. Rosner minimizes the amount of mathematical formulation (algebra-based) while still giving complete explanations of all the important concepts. As in previous editions, a major strength of this book is that every new concept is developed systematically through completely worked out examples from current medical research problems.

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Best APPLIED SPATIAL STATISTICS FOR PUBLIC HEALTH DATA

APPLIED SPATIAL STATISTICS FOR PUBLIC HEALTH DATA by JOHN WILEY AND SONS LTD




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Best Data Analysis and Statistics for Nursing Research

Data Analysis and Statistics for Nursing Research by Prentice Hall

Introductory text covers the statistical methods and procedures needed to analyze research findings. Special focus is given to quantitative methods. Other features include management of data, how to "clean" data, and how to work around missing data. Graduate nursing students.

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Best Air Pollution and Community Health: A Critical Review and Data Sourcebook (Industrial Health & Safety)

Air Pollution and Community Health: A Critical Review and Data Sourcebook (Industrial Health & Safety) by Van Nostrand Reinhold




Air Pollution and Community Health A Critical Review and Data Sourcebook Frederick W. Lipfert Air pollution has affected community health since the advent of the industrial age and arguably since the discovery of fire. While organized societies have taken important steps to reduce and control emissions, the quality of the air we breathe today remains a critical concern. Air Pollution and Community Health transforms the major epidemiological works of the past 40 years into a coherent picture of the effects of air pollution on respiration, hospitalization, and mortality. The book re-evaluates these studies to clarify their findings within a consistent analytical framework and to define statistical relationships between various measures of community health and air quality. Lipfert emphasizes observational studies and the quality of the data used. The book is organized by health endpoint rather than by pollutant, beginning with the major air pollution disasters that helped galvanize the environmental revolution. His analysis shows that community air pollution acts primarily to exacerbate existing conditions in susceptible individuals, rather than to create new cases of respiratory disease. He concludes that "the alarms that sounded over 40 years ago are still ringing"--substantial health risks are still presented by the current urban mixtures of air pollution. Many of the studies reviewed suggest that the current ambient air quality standards required by the Clean Air Act fail to protect the health of the most susceptible individuals. Further, because of the role of natural sources of air pollution, questions are raised as to whether complete protection can ever be achieved. The book presents data from many of the epidemiological studies reviewed, including those of the major disasters of 1930-1960. Graphical presentations are featured for easy reference; many new analyses are presented here for the first time. The book also includes introductory chapters on air pollution, statistical analysis, and respiratory physiology, for the convenience of readers who may not be well versed in all of these topics. The major technical chapters on mortality and hospitalization include reviews of the effects of air pollution episodes, time-series analyses, cross-sectional studies, and long-term studies of pollution abatement. The chapters on respiratory function include both the effects of air pollution on function and the role of lung function as an independent predictor of longevity. Air Pollution and Community Health presents one of the first comprehensive analyses of the subject. It should be used to re-examine the effectiveness of air pollution research and control policies in the United States and is essential reading for all professionals involved in air pollution control or public health.Read more Air Pollution and Community Health: A Critical Review and Data Sourcebook (Industrial Health & Safety)

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Survival Analysis: Techniques for Censored and Truncated Data (Statistics for Biology and Health) Description

Applied statisticians in many fields must frequently analyze time to event data. While the statistical tools presented in this book are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography, the focus here is on applications of the techniques to biology and medicine. The analysis of survival experiments is complicated by issues of censoring, where an individual's life length is known to occur only in a certain period of time, and by truncation, where individuals enter the study only if they survive a sufficient length of time or individuals are included in the study only if the event has occurred by a given date. The use of counting process methodology has allowed for substantial advances in the statistical theory to account for censoring and truncation in survival experiments. This book makes these complex methods more accessible to applied researchers without an advanced mathematical background. The authors present the essence of these techniques, as well as classical techniques not based on counting processes, and apply them to data. Practical suggestions for implementing the various methods are set off in a series of Practical Notes at the end of each section. Technical details of the derivation of the techniques are sketched in a series of Technical Notes. This book will be useful for investigators who need to analyze censored or truncated life time data, and as a textbook for a graduate course in survival analysis. The prerequisite is a standard course in statistical methodology.

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Clinical Data Mining and Warehousing, An Issue of Clinics in Laboratory Medicine, 1e (The Clinics: Internal Medicine) by Saunders




Clinical laboratory data are among the most detailed, objective, reliable and useful measures of patient characteristics contained in the medical record. The Editor's intent in assembling this volume is to provide an introduction to standard techniques for managing and mining clinical data, and to illustrate these techniques with several applications related to laboratory medicine and associated research. The volume is divided into a foundations section, which provides a discussion of data mining techniques and tools, data warehousing and time series analysis, and an applications section that presents a set of projects comprising data.Read more Clinical Data Mining and Warehousing, An Issue of Clinics in Laboratory Medicine, 1e (The Clinics: Internal Medicine)

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The latest edition of this best-selling textbook by Miles and Huberman not only is considerably expanded in content, but is now available in paperback. Bringing the art of qualitative analysis up-to-date, this edition adds hundreds of new techniques, ideas and references developed in the past decade. The increase in the use of computers in qualitative analysis is also reflected in this volume. There is an extensive appendix on criteria to choose from among the currently available analysis packages. Through examples from a host of social science and professional disciplines, Qualitative Data Analysis remains the most comprehensive and complete treatment of this topic currently available to scholars and applied researchers.

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Best Medical Statistics: A Guide to Data Analysis and Critical Appraisal

Medical Statistics: A Guide to Data Analysis and Critical Appraisal by BMJ Books




Holistic approach to understanding medical statistics

This hands-on guide is much more than a basic medical statistics introduction. It equips you with the statistical tools required for evidence-based clinical research.

Each chapter provides a clear step-by-step guide to each statistical test with practical instructions on how to generate and interpret the numbers, and present the results as scientific tables or graphs.

Showing you how to:

• analyse data with the help of data set examples (Click here to download datasets)
  
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Each statistical test is linked to the research question and the type of study design used. There are also checklists for critically appraising the literature and web links to useful internet sites.

Clear and concise explanations, combined with plenty of examples and tabulated explanations are based on the authors’ popular medical statistics courses. Critical appraisal guidelines at the end of each chapter help the reader evaluate the statistical data in their particular contexts.Read more Medical Statistics: A Guide to Data Analysis and Critical Appraisal

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Medical Statistics at a Glance

Experimental and Quasi-Experimental Designs for Generalized Causal Inference

Design Sensitivity: Statistical Power for Experimental Research (Applied Social Research Methods)

Scientific Writing: Easy When You Know How

Statistical Reasoning in Medicine: The Intuitive P-Value Primer

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The new edition adds a chapter on multiple linear regression in biomedical research, with sections including the multiple linear regressions model and least squares; the ANOVA table, parameter estimates, and confidence intervals; partial f-tests; polynomial regression; and analysis of covariance.
* Organized by problem rather than method, so it guides readers to the correct technique for solving the problem at hand.

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Applied Survival Analysis: Regression Modeling of Time to Event Data (Wiley Series in Probability and Statistics)

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THE MOST PRACTICAL, UP-TO-DATE GUIDE TO MODELLING AND ANALYZING TIME-TO-EVENT DATA—NOW IN A VALUABLE NEW EDITION

Since publication of the first edition nearly a decade ago, analyses using time-to-event methods have increase considerably in all areas of scientific inquiry mainly as a result of model-building methods available in modern statistical software packages. However, there has been minimal coverage in the available literature to9 guide researchers, practitioners, and students who wish to apply these methods to health-related areas of study. Applied Survival Analysis, Second Edition provides a comprehensive and up-to-date introduction to regression modeling for time-to-event data in medical, epidemiological, biostatistical, and other health-related research.

This book places a unique emphasis on the practical and contemporary applications of regression modeling rather than the mathematical theory. It offers a clear and accessible presentation of modern modeling techniques supplemented with real-world examples and case studies. Key topics covered include: variable selection, identification of the scale of continuous covariates, the role of interactions in the model, assessment of fit and model assumptions, regression diagnostics, recurrent event models, frailty models, additive models, competing risk models, and missing data.

Features of the Second Edition include:

• Expanded coverage of interactions and the covariate-adjusted survival functions
• The use of the Worchester Heart Attack Study as the main modeling data set for illustrating discussed concepts and techniques
• New discussion of variable selection with multivariable fractional polynomials
• Further exploration of time-varying covariates, complex with examples
• Additional treatment of the exponential, Weibull, and log-logistic parametric regression models
• Increased emphasis on interpreting and using results as well as utilizing multiple imputation methods to analyze data with missing values
• New examples and exercises at the end of each chapter

Analyses throughout the text are performed using Stata® Version 9, and an accompanying FTP site contains the data sets used in the book. Applied Survival Analysis, Second Edition is an ideal book for graduate-level courses in biostatistics, statistics, and epidemiologic methods. It also serves as a valuable reference for practitioners and researchers in any health-related field or for professionals in insurance and government.

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Life science data integration and interoperability is one of the most challenging problems facing bioinformatics today. In the current age of the life sciences, investigators have to interpret many types of information from a variety of sources: lab instruments, public databases, gene expression profiles, raw sequence traces, single nucleotide polymorphisms, chemical screening data, proteomic data, putative metabolic pathway models, and many others. Unfortunately, scientists are not currently able to easily identify and access this information because of the variety of semantics, interfaces, and data formats used by the underlying data sources.

Bioinformatics: Managing Scientific Data tackles this challenge head-on by discussing the current approaches and variety of systems available to help bioinformaticians with this increasingly complex issue. The heart of the book lies in the collaboration efforts of eight distinct bioinformatics teams that describe their own unique approaches to data integration and interoperability. Each system receives its own chapter where the lead contributors provide precious insight into the specific problems being addressed by the system, why the particular architecture was chosen, and details on the system's strengths and weaknesses. In closing, the editors provide important criteria for evaluating these systems that bioinformatics professionals will find valuable.

* Provides a clear overview of the state-of-the-art in data integration and interoperability in genomics, highlighting a variety of systems and giving insight into the strengths and weaknesses of their different approaches.
* Discusses shared vocabulary, design issues, complexity of use cases, and the difficulties of transferring existing data management approaches to bioinformatics systems, which serves to connect computer and life scientists.
* Written by the primary contributors of eight reputable bioinformatics systems in academia and industry including: BioKris, TAMBIS, K2, GeneExpress, P/FDM, MBM, SDSC, SRS, and DiscoveryLink.

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Hirsch and Riegelman have recognized the need for a text to explain, to a wide audience, statistical concepts rather than mathematics or terminology. They therefore expand on traditional mathematical methods by using graohics illustrating mathematical ideas, working through scores of examples from medical cases and literature, and employing non-technical terminology. Thus, they aim to provide the reader with an understanding of the terminology and mathematics without the rote learning that traditional methods require. The book presents the basic principles of statistics common to all methods of analysis and covers the logical processes used by statisticians to select statistical procedures for a particular set of data. Included is free software (STAT-PLUS) from the authors, and a free teacher's guide contains problems and answers, worked examples, flow charts and statistical tables.