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"Epidemiology Statistical methods."
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Monitoring the health of populations by tracking disease outbreaks : saving humanity from the next plague
\"Today the citizens of developed counties have never experienced a large-scale disease outbreak. One reason is the success of the public health community, including epidemiologists and biostatisticians, in tracking and identifying disease outbreaks. Monitoring the Health of Populations by Tracking Disease Outbreaks: Saving Humanity from the Next Plague is the story of the application of statistics for disease detection and tracking. The work of public health officials often critically depends on the use of statistical methods to help discern whether an outbreak may be occurring and, if there is sufficient evidence of an outbreak, then to locate and track it\"-- Provided by publisher.
Statistical advances in the biomedical sciences
by
Datta, Sujay
,
Biswas, Atanu
,
Fine, Jason P
in
Bioinformatics
,
Biology
,
Biology -- Research -- Statistical methods
2007,2008
The Most Comprehensive and Cutting-Edge Guide to Statistical Applications in Biomedical Research With the increasing use of biotechnology in medical research and the sophisticated advances in computing, it has become essential for practitioners in the biomedical sciences to be fully educated on the role statistics plays in ensuring the accurate analysis of research findings. Statistical Advances in the Biomedical Sciences explores the growing value of statistical knowledge in the management and comprehension of medical research and, more specifically, provides an accessible introduction to the contemporary methodologies used to understand complex problems in the four major areas of modern-day biomedical science: clinical trials, epidemiology, survival analysis, and bioinformatics. Composed of contributions from eminent researchers in the field, this volume discusses the application of statistical techniques to various aspects of modern medical research and illustrates how these methods ultimately prove to be an indispensable part of proper data collection and analysis. A structural uniformity is maintained across all chapters, each beginning with an introduction that discusses general concepts and the biomedical problem under focus and is followed by specific details on the associated methods, algorithms, and applications. In addition, each chapter provides a summary of the main ideas and offers a concluding remarks section that presents novel ideas, approaches, and challenges for future research. Complete with detailed references and insight on the future directions of biomedical research, Statistical Advances in the Biomedical Sciences provides vital statistical guidance to practitioners in the biomedical sciences while also introducing statisticians to new, multidisciplinary frontiers of application. This text is an excellent reference for graduate- and PhD-level courses in various areas of biostatistics and the medical sciences and also serves as a valuable tool for medical researchers, statisticians, public health professionals, and biostatisticians.
A practical approach to using statistics in health research : from planning to reporting
\"This book provides an outline with methodological steps of how to use statistics to analyze your research data. The book begins with a general introduction, which discusses what you should be trying to achieve with your statistical analysis. This involves describing the subjects you investigated and their outcomes, determining whether there is statistically significant evidence of differences in outcomes between groups of subjects, quantitatively describing effect sizes, and also determining whether any changes are large enough to be of clinical significance. Next, the authors cover data types and choosing statistical tests. This includes identifying the factor and outcome, and also identifying the type of data used to record the outcome. Readers are then introduced to multiple testing, the Chi-square test, and independent samples and the two-sample t-test. The Man-Whitney test is discussed, as well as the One-way ANOVA. Readers are taught how to Carrying out the Kruskal-Wallis test and the McNemar's test. The Paired t-test is covered, as well as how to carry out the Wilcoxon paired samples test. Readers are shown how to carry out the repeated measures ANOVA and the Friedman test. This includes discussion of merits of change in median, change in proportions in categories, and changes in high/low categories. The book concludes with a discussion on correlation and regression methods, and a detailed analysis on Cronbach's alpha\"-- Provided by publisher.
Applied longitudinal data analysis for epidemiology : a practical guide
by
Twisk, Jos W. R.
in
Epidemiology
,
Epidemiology -- Longitudinal studies
,
Epidemiology -- Research -- Statistical methods
2003
In this book the most important techniques available for longitudinal data analysis are discussed, including simple techniques such as the paired t-test and summary statistics, and more sophisticated techniques such as generalised estimating equations and random coefficient analysis. This practical guide is suitable for non-statisticians involved in medical research and epidemiology.
Radiation Dose Reconstruction for Epidemiologic Uses
by
National Research Council (U.S.). Committee on an Assessment of CDC Radiation Studies
in
Radiation dosimetry
,
Radiation injuries
,
Radiation injuries -- Epidemiology -- Statistical methods
2000,1995
Growing public concern about releases of radiation into the environment has focused attention on the measurement of exposure of people living near nuclear weapons production facilities or in areas affected by accidental releases of radiation.
Radiation-Dose Reconstruction for Epidemiologic Uses responds to the need for criteria for dose reconstruction studies, particularly if the doses are to be useful in epidemiology. This book provides specific and practical recommendations for whether, when, and how studies should be conducted, with an emphasis on public participation.
Based on the expertise of scientists involved in dozens of dose reconstruction projects, this volume:
Provides an overview of the basic requirements and technical aspects of dose reconstruction.
Presents lessons to be learned from dose reconstructions after Chernobyl, Three Mile Island, and elsewhere.
Explores the potential benefits and limitations of biological markers.
Discusses how to establish the \"source term\"-that is, to determine what was released.
Explores methods for identifying the environmental pathways by which radiation reaches the body.
Offers details on three major categories of dose assessment.
Applied Longitudinal Data Analysis for Epidemiology
by
Twisk, Jos W. R.
in
Epidemiology
,
Epidemiology -- Longitudinal studies
,
Epidemiology -- Research -- Statistical methods
2013
This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.
Applied longitudinal data analysis for epidemiology
by
Twisk, Jos W. R
in
Epidemiology
2013
This book discusses the most important techniques available for longitudinal data analysis, from simple techniques such as the paired t-test and summary statistics, to more sophisticated ones such as generalized estimating of equations and mixed model analysis. A distinction is made between longitudinal analysis with continuous, dichotomous and categorical outcome variables. The emphasis of the discussion lies in the interpretation and comparison of the results of the different techniques. The second edition includes new chapters on the role of the time variable and presents new features of longitudinal data analysis. Explanations have been clarified where necessary and several chapters have been completely rewritten. The analysis of data from experimental studies and the problem of missing data in longitudinal studies are discussed. Finally, an extensive overview and comparison of different software packages is provided. This practical guide is essential for non-statisticians and researchers working with longitudinal data from epidemiological and clinical studies.
Statistical methods in genetic epidemiology
2004
This well-organized and clearly written text has a unique focus on methods of identifying the joint effects of genes and environment on disease patterns. It follows the natural sequence of research, taking readers through the study designs and statistical analysis techniques for determining whether a trait runs in families, testing hypotheses about whether a familial tendency is due to genetic or environmental factors or both, estimating the parameters of a genetic model, localizing and ultimately isolating the responsible genes, and finally characterizing their effects in the population. Examples from the literature on the genetic epidemiology of breast and colorectal cancer, among other diseases, illustrate this process. Although the book is oriented primarily towards graduate students in epidemiology, biostatistics and human genetics, it will also serve as a comprehensive reference work for researchers. Introductory chapters on molecular biology, Mendelian genetics, epidemiology, statistics, and population genetics will help make the book accessible to those coming from one of these fields without a background in the others. It strikes a good balance between epidemiologic study designs and statistical methods of data analysis.
Bayesian Methods in Epidemiology
by
Broemeling, Lyle D.
in
Bayesian statistical decision theory
,
Epidemiology
,
Epidemiology -- Statistical methods
2014,2013
Written by a biostatistics expert with over 20 years of experience in the field, this book is the first to introduce epidemiology from a Bayesian perspective. It shows epidemiologists how Bayesian models and techniques are useful in studying the association between disease and exposure to risk factors. With many examples and end-of-chapter exercises, the book employs the software package WinBUGS to carry out the analyses and offers the code in the text and for download online.