Download or read book A Practical Guide to Applied Biostatistics written by Mohammadali M. Shoja and published by Wiley-Blackwell. This book was released on 2014-05-20 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Applied Biostatistics: A Practical Guide to Data Management in Scientific Research provides a fast, practical and independent learning tool that allows the reader to understand the indications and applications of statistics. Each chapter starts with definitions and a general overview of the statistical methods or methods of interest. A table of to-be-discussed statistical tests, their utilities and examples of the application are provided, followed by different research scenarios and lists of related hypotheses to be tested. Next, the potentially applicable statistical tests and their assumptions will be discussed to an extent necessary to obtain a clear understanding of the utility and indications of each statistical test, and finally the guidelines for interpretation of analysis output and how to report the findings are explored. Written in a reader-friendly style which will be accessible to students as well as experienced scientists who want to brush up on their statistics, the Handbook of Applied Biostatistics will be the go-to statistical method resource for graduate students in all biological and clinical disciplines.
Download or read book Applied Mixed Model Analysis written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2019-04-18 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing interpretation of results, this hands-on guide explains why, when, and how to use mixed models with your data.
Download or read book Practical Biostatistics written by Mendel Suchmacher and published by Academic Press. This book was released on 2012-07-26 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods and outcomes to drive further experimentation and diagnosis. The profusion of evidence-based medicine in medical practice and clinical research has produced a need for life scientists and clinical researchers to assimilate biostatistics into their work to meet efficacy and practical standards. Practical Biostatistics provides researchers, medical professionals, and students with a friendly, practical guide to biostatistics. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or a hands-on guide to effectively incorporate biostatistics in clinical trials. Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines Clear and concise definitions and examples provide a pragmatic guide to bring clarity to the applications of statistics in improving human health Addresses the challenge of assimilation of mathematical concepts to better interpret literature, to build stronger studies, to present research effectively, and to improve communication with supporting biostatisticians
Download or read book Biostatistics Using JMP written by Trevor Bihl and published by SAS Institute. This book was released on 2017-10-03 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Analyze your biostatistics data with JMP! Trevor Bihl's Biostatistics Using JMP: A Practical Guide provides a practical introduction on using JMP, the interactive statistical discovery software, to solve biostatistical problems. Providing extensive breadth, from summary statistics to neural networks, this essential volume offers a comprehensive, step-by-step guide to using JMP to handle your data. The first biostatistical book to focus on software, Biostatistics Using JMP discusses such topics as data visualization, data wrangling, data cleaning, histograms, box plots, Pareto plots, scatter plots, hypothesis tests, confidence intervals, analysis of variance, regression, curve fitting, clustering, classification, discriminant analysis, neural networks, decision trees, logistic regression, survival analysis, control charts, and metaanalysis. Written for university students, professors, those who perform biological/biomedical experiments, laboratory managers, and research scientists, Biostatistics Using JMP provides a practical approach to using JMP to solve your biostatistical problems.
Download or read book Biostatistical Design and Analysis Using R written by Dr Murray Logan and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: R — the statistical and graphical environment is rapidly emerging as an important set of teaching and research tools for biologists. This book draws upon the popularity and free availability of R to couple the theory and practice of biostatistics into a single treatment, so as to provide a textbook for biologists learning statistics, R, or both. An abridged description of biostatistical principles and analysis sequence keys are combined together with worked examples of the practical use of R into a complete practical guide to designing and analyzing real biological research. Topics covered include: simple hypothesis testing, graphing exploratory data analysis and graphical summaries regression (linear, multi and non-linear) simple and complex ANOVA and ANCOVA designs (including nested, factorial, blocking, spit-plot and repeated measures) frequency analysis and generalized linear models. Linear mixed effects modeling is also incorporated extensively throughout as an alternative to traditional modeling techniques. The book is accompanied by a companion website www.wiley.com/go/logan/r with an extensive set of resources comprising all R scripts and data sets used in the book, additional worked examples, the biology package, and other instructional materials and links.
Download or read book Applied Statistics with R written by Justin C. Touchon and published by Oxford University Press. This book was released on 2021 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the 'go-to' stats program throughout the life-sciences. Furthermore, by using a single, real-world dataset throughout the book, readers are encouraged to become deeply familiar with an imperfect but realistic set of data. - -
Download or read book Preventing and Treating Missing Data in Longitudinal Clinical Trials written by Craig H. Mallinckrodt and published by Cambridge University Press. This book was released on 2013-01-28 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on the prevention and treatment of missing data in longitudinal clinical trials, looking at key principles and explaining analytic methods.
Download or read book Applied Longitudinal Data Analysis for Epidemiology written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2013-05-09 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.
Download or read book Basic Statistics and Epidemiology written by Antony Stewart and published by Radcliffe Publishing. This book was released on 2007 with total page 176 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide in basic statistics emphasises its practical use in epidemiology and public health, providing understanding of topics such as study design, data analysis and statistical methods used in the execution of medical research. This title includes sections on Correlation and Linear Regression, as well as exercises reflecting working life.
Download or read book Applied Biostatistics for the Health Sciences written by Richard J. Rossi and published by John Wiley & Sons. This book was released on 2022-04-27 with total page 692 pages. Available in PDF, EPUB and Kindle. Book excerpt: APPLIED BIOSTATISTICS FOR THE HEALTH SCIENCES In this newly revised edition of Applied Biostatistics for the Health Sciences, accomplished statistician Dr. Richard Rossi delivers a robust and easy-to-understand exploration of statistics in the context of applied health science and biostatistics. The book covers sample design, logistic regression, experimental design, survival analysis, basic statistical computation, and many more topics with a strong focus on the correct use and interpretation of statistics. The author also explains how to assess the quality of observed data, how to collect quality data, and the use of confidence intervals in conjunction with hypothesis and significance tests. A thorough introduction to biostatistics, including explanations of fundamental concepts like populations, samples, statistics, biomedical studies, and data set examples A comprehensive exploration of population descriptions, including qualitative and quantitative variables, multivariate data, measures of dispersion, and probability Practical discussions of random sampling, summarizing random samples, and the measurement of the reliability of statistics In-depth examinations of confidence intervals, statistical hypothesis testing, simple and multiple linear regression, and experimental design Perfect for health science and biostatistics students and professors at the upper undergraduate and graduate levels, Applied Biostatistics for the Health Sciences is also a must-read reference for practitioners and professionals in the fields of pharmacy, biochemistry, nursing, health care informatics, and the applied health sciences.
Download or read book Concise Biostatistical Principles Concepts written by Laurens Holmes, Jr. and Franklin Opara and published by Author House. This book was released on 2014-03 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biostatistics deals with making sense of data. While statistical inference is essential in our application of the research findings to clinical decision-making regarding the care of our patients, statistical inference without clinical relevance or importance can be very misleading and even meaningless. This textbook has attempted to deemphasize p value in the interpretation of clinical and biomedical data by stressing the importance of confidence intervals, which allow for the quantification of evidence. For example, a large study due to a large sample size that minimizes variability may show a statistically significant difference while in reality the difference is too insignificant to warrant any clinical relevance. Covers these relevant topics in biostatistics: Design Process, Sampling & Reality in Statistical Modeling Basics of Biostatistical Reasoning & Inference Central Tendency Theorem & Measures of Dispersion Most commonly used & abused parametric test - t test Most commonly used & abused non-parametric test - chi squared statistic Sample size and power estimations Logistic/Binomial Regression Models - Binary Outcomes Time-to-Event Data - Survival Analysis & Count Data - Poisson Regression ANOVA, ANCOVA - Mixed Effects Model (Fixed and Random), RANOVA, GEE Simple & Multiple Linear Regression Models Correlation Analysis (Pearson & Spearman Rank) Clinical & Statistical Significance - p value as a function of sample size Clinical and biomedical researchers often ignore an important aspect of evidence discovery from their funded or unfunded projects. Since the attempt is to illustrate some sets of relationships from the data set, researchers often do not exercise substantial amount of time in assessing the reliability and validity of the data to be utilized in the analysis. However, the expected inference or the conclusion to be drawn is based on the analysis of the un-assessed data. Reality in statistical modeling of biomedical and clinical research data remains the focus of scientific evidence discovery, and this book. This text is written to highlight the importance of appropriate design prior to analysis by placing emphasis on subject selection and probability sample and the randomization process when applicable prior to the selection of the analytic tool. In addition, this book stresses the importance of biologic and clinical significance in the interpretation of study findings. The basis for statistical inference, implying the quantification of random error is random sample, which had been perpetually addressed in this book. When studies are conducted without a random sample, except when disease registries/databases or consecutive subjects are utilized, as often encountered in clinical and biomedical research, it is meaningless to report the findings with p value.
Download or read book Resampling Methods written by Phillip I. Good and published by Springer Science & Business Media. This book was released on 2006-12-31 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware. New to the third edition are additional program listings and screen shots of C++, CART, Blossom, Box Sampler (an Excel add-in), EViews, MATLAB, R, Resampling Stats, SAS macros, S-Plus, Stata, or StatXact, which accompany each resampling procedure. A glossary and solutions to selected exercises have also been added. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
Download or read book Secondary Data Sources for Public Health written by Sarah Boslaugh and published by Cambridge University Press. This book was released on 2007-04-09 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: Secondary data play an increasingly important role in epidemiology and public health research and practice; examples of secondary data sources include national surveys such as the BRFSS and NHIS, claims data for the Medicare and Medicaid systems, and public vital statistics records. Although a wealth of secondary data is available, it is not always easy to locate and access appropriate data to address a research or policy question. This practical guide circumvents these difficulties by providing an introduction to secondary data and issues specific to its management and analysis, followed by an enumeration of major sources of secondary data in the United States. Entries for each data source include the principal focus of the data, years for which it is available, history and methodology of the data collection process, and information about how to access the data and supporting materials, including relevant details about file structure and format.
Download or read book Analysis of Data from Randomized Controlled Trials written by Jos W.R. Twisk and published by Springer Nature. This book was released on 2021-10-15 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a practical guide to the analysis of data from randomized controlled trials (RCT). It gives an answer to the question of how to estimate the intervention effect in an appropriate way. This problem is examined for different RCT designs, such as RCTs with one follow-up measurement, RCTs with more than one follow-up measurement, cluster RCTs, cross-over trials, stepped wedge trials, and N-of-1 trials. The statistical methods are explained in a non-mathematical way and are illustrated by extensive examples. All datasets used in the book are available for download, so readers can reanalyse the examples to gain a better understanding of the methods used. Although most examples are taken from epidemiological and clinical studies, this book is also highly recommended for researchers working in other fields.
Download or read book Biomeasurement written by Dawn Hawkins and published by Oxford University Press, USA. This book was released on 2014-04 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offering a student-focused introduction to the use of statistics in the study of the biosciences, this text looks at statistical techniques and other essential tools for bioscientists, giving students the confidence to use and further explore the key techniques for themselves.
Download or read book Applied Multilevel Analysis written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2006-03-28 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a practical introduction to multilevel analysis suitable for all those doing research. Most books on multilevel analysis are written by statisticians; those books are difficult for non-mathematical researchers. In contrast, this volume provides an accessible account on the practical application of multilevel analysis in research. Many worked examples, with computer output, are given to illustrate and explain this subject. Datasets of the examples are available on the internet, so the reader can reanalyze the data. This approach will help bridge the conceptual and communication gap that exists between researchers and statisticians.
Download or read book Applied Multilevel Analysis written by Jos W. R. Twisk and published by Cambridge University Press. This book was released on 2006-04-06 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a practical introduction to multilevel analysis, written for non-mathematicians.
