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Statistical Questions in Evidence-based Medicine is a companion volume to the new edition of An Introduction to Medical Statistics and includes questions and answers which are complementary to the textbook. This new book takes a practical approach that develops an understanding of statistics and suggests appropriate questions to ask about research methods, figures and conclusions and whether they are evidence based. The book is a model of clarity and common sense in what is frequently an unnecessarily obscure area of science. It looks at the application of and provides a critique of statistics, encouraging an evidence-based approached to medical statistics. Through the critical evaulation of the published medical literature, the text will enable both students and researchers to understand the appropriate use of descriptive and inferential statistics in study design and when writing papers. The reproduction of short excerpts of material from published papers or summaries of their results are included and they are considered in a question and answer format. The reader can either read through the series of cases and follow through worked examples or work through the book themselves as a series of exercises. The questions are clearly graded, through the use of icons, in terms of difficulty into standard and postgraduate levels. This book will prove invaluable to students, medical researchers and doctors alike.
Now in its Fourth Edition, An Introduction to Medical Statistics continues to be a 'must-have' textbook for anyone who needs a clear logical guide to the subject. Written in an easy-to-understand style and packed with real life examples, the text clearly explains the statistical principles used in the medical literature. Taking readers through the common statistical methods seen in published research and guidelines, the text focuses on how to interpret and analyse statistics for clinical practice. Using extracts from real studies, the author illustrates how data can be employed correctly and incorrectly in medical research helping readers to evaluate the statistics they encounter and appropriately implement findings in clinical practice. End of chapter exercises, case studies and multiple choice questions help readers to apply their learning and develop their own interpretative skills. This thoroughly revised edition includes new chapters on meta-analysis, missing data, and survival analysis.
The accompanying CD-ROM contains clinical examples, critical appraisals and background papers.
Statistics and evidence-based medicine are assessed in most postgraduate and undergraduate medical examinations and degrees in health sciences. All clinicians have to acquire skills in this area. This book aims to provide a brief overview of basic medical statistics and the numerical aspects of evidence-based medicine, to give realistic worked examples to illustrate the interpretation of studies relevant to clinical practice, and to allow examination practice. It aims to cover all major topics covered in the undergraduate and postgraduate examinations.Each chapter begins with an overview and summary of the main points, followed by worked examples and exercises with full answers. It will be ideal for all postgraduate medical examination candidates. Other clinicians and undergraduate students in medicine and health sciences will also find it useful.
The best-selling introduction to evidence-based medicine In a clear and engaging style, How to Read a Paper demystifies evidence-based medicine and explains how to critically appraise published research and also put the findings into practice. An ideal introduction to evidence-based medicine, How to Read a Paper explains what to look for in different types of papers and how best to evaluate the literature and then implement the findings in an evidence-based, patient-centred way. Helpful checklist summaries of the key points in each chapter provide a useful framework for applying the principles of evidence-based medicine in everyday practice. This fifth edition has been fully updated with new examples and references to reflect recent developments and current practice. It also includes two new chapters on applying evidence-based medicine with patients and on the common criticisms of evidence-based medicine and responses. How to Read a Paper is a standard text for medical and nursing schools as well as a friendly guide for everyone wanting to teach or learn the basics of evidence-based medicine.
Statistics for Evidence-Based Practice in Nursing, Second Edition presents statistics in a readable, user-friendly manner for both graduate students and the professional nurse.
Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a "large" trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement.
This essential book details intermediate-level statistical methods and frameworks for the clinician and medical researcher with an elementary grasp of health statistics and focuses on selecting the appropriate statistical method for many scenarios. Detailed evaluation of various methodologies familiarizes readers with the available techniques and equips them with the tools to select the best from a range of options. The inclusion of a hypothetical case study between a clinician and statistician charting the conception of the research idea through to results dissemination enables the reader to understand how to apply the concepts covered into their day-to-day clinical practice. Applied Statistical Considerations for Clinical Researchers focuses on how clinicians can approach statistical issues when confronted with a medical research problem by considering the data structure, how this relates to their study's aims and any potential knock-on effects relating to the evidence required to make correct clinical decisions. It covers the application of intermediate-level techniques in health statistics making it an ideal resource for the clinician seeking an up-to-date resource on the topic.
The first edition of Basic Statistics and Pharmaceutical Statistical Applications successfully provided a practical, easy-to-read, basic statistics book. This second edition not only updates the previous edition, but expands coverage in the area of biostatistics and how it relates to real-world professional practice. Taking you on a roller coaster ride through the world of statistics, Dr. De Muth clearly details the methodology necessary to summarize data and make informed decisions about observed outcomes. What's new or different in the Second Edition? New chapters cover: Measures of association primarily with nominal and ordinal data and and more than 15 tests Survival statistics including actuarial analysis and an introduction to multiple regression with survival data using proportional hazards regression An introduction to the topic of evidence-based practice with discussions of sensitivity and specificity, predictive values, and likelihood ratios Odds ratios and relative risk ratios that provide valuable information for dealing with probability, odds, and risk New sections address Power and sample size determination for two-sample Z-tests of proportions Clinical equivalence and noninferiority studies, process capability, and tolerance limits Methods for assessing repeatability and reproducibility Expanded information includes: Chi square, repeated measures designs, Latin Square designs, nine multiple comparison tests, and outlier testing Inverse prediction with linear regression, handling of multiple data points at different levels of independent variable, and assessment of parallelism of slopes for two samples Additional types of bivariate correlations and various assessments for independence and randomness More nonparametric tests including new information on post hoc comparisons for a significant Kruskal-Wallis test, the Kolmogorov-Smirnov goodness-of-fit test, and the Anderson-Darling test, as well as runs and range tests Eight new tables useful for the interpretation of some of the new inferential statistics De Muth provides concrete examples that enable you to effectively manage information in your day-to-day problem solving and reporting of findings. By avoiding heavy-duty mathematics and theory, even the mathematically challenged can benefit and increase their confidence in using statistics procedures.
Organized to present a comprehensive overview of the field of cardiology in an accessible, reader-friendly format that can be covered in about 12 months, this new edition contains roughly 50% new material, the cardiac pharmacology section has been completely reworked, cardiovascular trials have been included, and the entire book has been updated to reflect current practice guidelines and recent developments. The book is peppered throughout with numerous tables and clinical pearls that aid the student, as well as the teacher, to remain focused.