Basic Statistics and Epidemiology: A Practical Guide, Fourth Edition

 Epidemiology, Statistics  Comments Off on Basic Statistics and Epidemiology: A Practical Guide, Fourth Edition
Feb 262019
 

Basic Statistics and Epidemiology is a straightforward primer in basic statistics that emphasizes its practical use in epidemiology and public health, providing an understanding of essential topics such as study design, data analysis and statistical methods used in the execution of medical research.

Assuming no prior knowledge, the clarity of the text and care of presentation ensure those new to, or challenged by, these topics are given a thorough introduction without being overwhelmed by unnecessary detail. An understanding and appreciation of statistics is central to ensuring that professional practice is based on the best available evidence, in order to treat and help most appropriately the wider community. By reading this book, students, researchers, doctors, nurses and health managers will have the knowledge necessary to understand and apply the tools of statistics and epidemiology to their own practice.

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Statistics at Square One, 11th edition

 Statistics  Comments Off on Statistics at Square One, 11th edition
Feb 252019
 

The new edition of this international bestseller continues to throw light on the world of statistics for health care professionals and medical students.Revised throughout, the 11th edition features new material in the areas ofrelative risk, absolute risk and numbers needed to treatdiagnostic tests, sensitivity, specificity, ROC curvesfree statistical softwareThe popular self-testing exercises at the end of every chapter are strengthened by the addition of new sections on reading and reporting statistics and formula appreciation.

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Biostatistical Methods

 Statistics  Comments Off on Biostatistical Methods
Feb 162019
 

The use of biostatistical techniques in molecular biology has grown tremendously in recent years and is now essential for the correct interpretation of a wide variety of laboratory studies. In Biostatistical Methods, a panel of leading biostatisticians and biomedical researchers describe all the key techniques used to solve commonly occurring analytical problems in molecular biology, and demonstrate how these methods can identify new markers for exposure to a risk factor, or for determining disease outcomes. Major areas of application include microarray analysis, proteomic studies, image quantitation, determining new disease biomarkers, and designing studies with adequate levels of statistical power. In the case of genetic effects in human populations, the authors describe sophisticated statistical methods to control the overall false-positive rate when many statistical tests are used in linking particular alleles to the occurrence of disease. Other methods discussed are those used to validate statistical approaches for analyzing the E-D association, to study the associations between disease and the inheritance of particular genetic variants, and to examine real data sets. There are also useful recommendations for statistical and data management software (JAVA, Oracle, S-Plus, STATA, and SAS) . Accessible, state-of-the-art, and highly practical,  Methods provides an excellent starting point both for statisticians just beginning work on problems in molecular biology, and for all molecular biologists who want to use biostatistics in genetics research designed to uncover the causes and treatments of disease.
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Statistical Development of Quality in Medicine

 Statistics  Comments Off on Statistical Development of Quality in Medicine
Feb 022019
 

The promotion of standards and guidelines to advance quality assurance and control is an integral part of the health care sector. Quantitative methods are needed to monitor, control and improve the quality of medical processes. Statistical Development of Quality in Medicine presents the statistical concepts behind the application of industrial quality control methods. Filled with numerous case studies and worked examples, the text enables the reader to choose the relevant control chart, to critically apply it, improve it if necessary, and monitor its stability. Furthermore, the reader is provided with the necessary background to critically assess the literature on the application of control charts and risk adjustment and to apply the findings. Contains a user-friendly introduction, setting out the necessary statistical concepts used in the field. Uses numerous real-life case studies from the literature and the authors’ own research as the backbone of the text. Provides a supplementary website featuring problems and answers drawn from the book, alongside examples in Statgraphics. The accessible style of Statistical Development of in Clinical Medicine invites a large readership. It is primarily aimed at health care officials, and personnel responsible for developing and controlling the quality of health care services. However, it is also ideal for statisticians working with health care problems, diagnostic and pharmaceutical companies, and graduate students of quality control.Content: Chapter 1 Theory of Statistical Process Control (pages 9–36): Chapter 2 Shewhart Control Charts (pages 37–77): Chapter 3 Time?Weighted Control Charts (pages 78–91): Chapter 4 Control Charts for Autocorrelated Data (pages 92–109): Chapter 5 Tools for Risk Adjustment (pages 111–148): Chapter 6 Risk?Adjusted Control Charts (pages 149–163): Chapter 7 Risk?Adjusted Comparison of Healthcare Providers (pages 164–181): Chapter 8 Learning Curves (pages 183–194): Chapter 9 Assessing the Quality of Clinical Processes (pages 195–215):
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Statistical Methods for Microarray Data Analysis: Methods and Protocols

 Statistics  Comments Off on Statistical Methods for Microarray Data Analysis: Methods and Protocols
Nov 072018
 


Microarrays for simultaneous measurement of redundancy of RNA species are used in fundamental biology as well as in medical research. Statistically,a microarray may be considered as an observation of very high dimensionality equal to the number of expression levels measured on it.

In Statistical Methods for Microarray Data Analysis: Methods and Protocols, expert researchers in the field detail many methods and techniques used to study microarrays, guiding the reader from microarray technology to statistical problems of specific multivariate data analysis. Written in the highly successful Methods in Molecular Biology™ series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Statistical Methods for Microarray Data Analysis: Methods and Protocols aids scientists in continuing to study microarrays and the most current statistical methods.

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The statistical evaluation of medical tests for classification and prediction

 Statistics  Comments Off on The statistical evaluation of medical tests for classification and prediction
Oct 132018
 

This book describes statistical concepts and techniques for evaluating medical diagnostic tests and biomarkers for detecting disease. More generally, the techniques pertain to the statistical classification problem for predicting a dichotomous outcome. Measures for quantifying test accuracy are described including sensitivity, specificity, predictive values, diagnostic likelihood ratios and the Receiver Operating Characteristic Curve that is commonly used for continuous and ordinal valued tests. Statistical procedures are presented for estimating and comparing them. Regression frameworks for assessing factors that influence test accuracy and for comparing tests while adjusting for such factors are presented. This book presents many worked examples of real data and should be of interest to practicing statisticians or quantitative researchers involved in the development of tests for classification or prediction in medicine.
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Applied Biostatistical Principles and Concepts: Clinicians’ Guide to Data Analysis and Interpretation

 Statistics  Comments Off on Applied Biostatistical Principles and Concepts: Clinicians’ Guide to Data Analysis and Interpretation
Sep 252018
 

The past three decades have witnessed modern advances in statistical modeling and evidence discovery in biomedical, clinical, and population-based research. With these advances come the challenges in accurate model stipulation and application of models in scientific evidence discovery

Applied Biostatistical Principles and Concepts provides practical knowledge using biological and biochemical specimen/samples in order to understand health and disease processes at cellular, clinical, and population levels. Concepts and techniques provided will help researchers design and conduct studies, then translate data from bench to clinics in attempt to improve the health of patients and populations.

This book is suitable for both clinicians and health or biological sciences students. It presents the reality in statistical modelling of health research data in a concise manner that will address the issue of “big data” type I error tolerance and probability value, effect size and confidence interval for precision, effect measure modification and interaction as well as confounders, thus allowing for more valid inferences and yielding results that are more reliable, valid and accurate.

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Medical Statistics: An A-Z Companion, Second Edition

 Statistics  Comments Off on Medical Statistics: An A-Z Companion, Second Edition
Sep 242018
 

This invaluable, jargon-free guide to essential medical terminology in an accessible A-Z format is ideal for medical, allied health and biomedical science students and researchers, clinicians and health care practitioners. Avoiding the complex language that is so often a feature of statistics and research methodology, this text provides clear and succinct explanations, clarifying meaning and showing the interdependencies between important concepts. This edition includes enhanced explanations of statistical concepts and methods―including more illustrative content―for greater accessibility. The book makes frequent use of examples from the medical literature, with reference to landmark studies, ensuring clinical relevance. It remains an ideal aid to accompany the reading and critical appraisal of medical and health care literature, now widely recognized to be a practical lifelong skill required by all health professionals throughout undergraduate and postgraduate studies and during clinical practice.
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Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered, and Other Repeated Measures Data

 Statistics  Comments Off on Statistical Methods in Psychiatry and Related Fields: Longitudinal, Clustered, and Other Repeated Measures Data
Sep 212018
 

Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, there is natural heterogeneity in treatment responses and in other characteristics in the populations. Simple statistical methods do not work well with such data. More advanced statistical methods capture the data complexity better, but are difficult to apply appropriately and correctly by investigators who do not have advanced training in statistics. This book presents, at a non-technical level, several approaches for the analysis of correlated data: mixed models for continuous and categorical outcomes, nonparametric methods for repeated measures and growth mixture models for heterogeneous trajectories over time. Separate chapters are devoted to techniques for multiple comparison correction, analysis in the presence of missing data, adjustment for covariates, assessment of mediator and moderator effects, study design and sample size considerations. The focus is on the assumptions of each method, applicability and interpretation rather than on technical details. The intended audience are applied researchers with minimal knowledge of statistics, although the book could also benefit collaborating statisticians. The book, together with the online materials, is a valuable resource aimed at promoting the use of appropriate statistical methods for the analysis of repeated measures data.
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Modern Bayesian Statistics in Clinical Research

 Statistics  Comments Off on Modern Bayesian Statistics in Clinical Research
Sep 182018
 

The current textbook has been written as a help to medical / health professionals and students for the study of modern Bayesian statistics, where posterior and prior odds have been replaced with posterior and prior likelihood distributions. Why may likelihood distributions better than normal distributions estimate uncertainties of statistical test results? Nobody knows for sure, and the use of likelihood distributions instead of normal distributions for the purpose has only just begun, but already everybody is trying and using them. SPSS statistical software version 25 (2017) has started to provide a combined module entitled Bayesian Statistics including almost all of the modern Bayesian tests (Bayesian t-tests, analysis of variance (anova), linear regression, crosstabs etc.).

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