NUR 520: Epidemiological & Biostatistical Applications in Healthcare
“This Library Research Guide is intended to help you identify and locate scholarly and evidence-based resources (ebooks, articles, websites,etc.) on the subject of epidemiology and biostatistics. On this guide, you'll also find info on data sources, prof
Epidemiology
from Gale Encyclopedia of Public Health
"Epidemiology is the branch of medicine and public health that concerns the study of factors associated with either communicable or noncommunicable diseases that affect the health of populations rather than individuals." Read more about epidemiology This link opens in a new window.
Epidemiology and Geography by Call Number: Available OnlineISBN: 9781119597445Publication Date: 2019
Modern Epidemiology by
Selected as a Doody's Core Title for 2022! Now in a fully revised 4th Edition, Modern Epidemiology remains the gold standard text in this complex and evolving field, offering unparalleled, comprehensive coverage of the principles and methods of epidemiologic research. Featuring a new, full-color design, updated models, and a new format allowing space for margin notes, this edition continues to provide authoritative information on the methodologic issues crucial to the wide range of epidemiologic applications in public health and medicine. Reflects both the conceptual development of this evolving science and the increasing role that epidemiology plays in both public health and medicine. Features a new full-color design, new coverage of marginal structural models, new instrumental variable analysis, updated structural nested models, and more. Covers a broad range of concepts and methods, including epidemiologic measures of occurrence and effect, study designs, validity, precision, statistical interference, field methods, and causal diagrams. Includes data analysis topics such as Bayesian analysis, sensitivity analysis, and bias analysis, with an extensive overview of modern regression methods including logistic and survival regression, splines, hierarchical (multilevel) regression, propensity scores and other scoring methods, and g-estimation. Discusses special topics such as disease surveillance, ecologic studies, social epidemiology, infectious disease epidemiology, genetic and molecular epidemiology, nutritional epidemiology, environmental epidemiology, reproductive epidemiology, clinical epidemiology, and meta-analysis. Coauthored by three leading epidemiologists, with contributions from experts in a variety of epidemiologic sub-disciplines.
Call Number: Available OnlineISBN: 9781451193282Publication Date: 2021
Preparing for Pandemics in the Modern World by Call Number: Available OnlineISBN: 9781623499464Publication Date: 2020
Biostatistics
from International Encyclopedia of Public Health
"The role of statistics in public health research and practice is much as it is with other sciences; its methods assist in the design of studies and in their interpretation by dealing probabilistically with variation in measurements." Read more about biostatistics This link opens in a new window.
Advances in Bioinformatics, Biostatistics and Omic Sciences by Bioinformatics, and by extension omic sciences - the collective disciplines that are dependent on the use of extensive datasets of biological information - present a challenge of data management for researchers all over the world. Big data collected as part of research projects and experiments can be complex, with several kinds of variables involved. Coupled with continuously changing bioinformatics and information technology tools, there is a need to bring a multidisciplinary approach into these fields. Advances in Bioinformatics, Biostatistics and Omic Sciences attempts to realize an integrated approach between all omic sciences, exploring innovative bioinformatics and biostatistical methodologies which enable researchers to unveil hidden sides of biological phenomena. This volume presents reviews on the following topics which give a glimpse of recent advances in the field:- New Integrated Mitochondrial DNA Bioinformatics Pipeline to Improve Quality Assessment of Putative Pathogenic Variants from NGS Experiments - Variant Calling on RNA Sequencing Data: State of Art and Future Perspectives - An innovative Gene Prioritization Pipeline for WES analyses - New Integrated Differential Expression Approach for RNA-Seq Data Analysis - Innovations in Data Visualization for Straightforward Interpretation of Nucleic Acid Omics Outcomes This volume serves as a guide for graduate students in bioinformatics as well as researchers planning new projects as a part of their professional and academic activities.
Call Number: Available OnlineISBN: 9789811481789Publication Date: 2020
Biostatistics for Epidemiology and Public Health Using R by
Since it first appeared in 1996, the open-source programming language R has become increasingly popular as an environment for statistical analysis and graphical output. This is the first textbook to present classical biostatistical analysis for epidemiology and related public health sciences to students using the R language. Based on the assumption that readers have minimal familiarity with statistical concepts, the author uses a step-by-step approach to building skills. The text encompasses biostatistics from basic descriptive and quantitative statistics to survival analysis and missing data analysis in epidemiology. Illustrative examples, including real-life research problems drawn from such areas as nutrition, environmental health, and behavioral health, engage students and reinforce the understanding of R. These examples illustrate the replication of R for biostatistical calculations and graphical display of results. The text covers both essential and advanced techniques and applications in biostatistics that are relevant to epidemiology. Also included are an instructor's guide, student solutions manual, and downloadable data sets. Key Features: First overview biostatistics textbook for epidemiology and public health that uses the open-source R program Covers essential and advanced techniques and applications in biostatistics as relevant to epidemiology Features abundant examples to illustrate the application of R language for biostatistical calculations and graphical displays of results Includes instructor's guide, student solutions manual, and downloadable data sets.
Call Number: Online BookISBN: 9780826110268Publication Date: 2016Introduction to Biotechnology and Biostatistics by Introduction to Biotechnology and Biostatistics is a book which introduces the concept of biotechnology and biostatistics. Different terms such as genes, genomes and genetic engineering and recombinant DNA technology have been described in this book. This book highlights the important of genetic engineering in the human welfare and the concept of animal biotechnology as well as plant biotechnology. This book aims to discuss about the concept of industrial biotechnology, environmental biotechnology and the biosafety guidelines for the intellectual property rights and entrepreneurship development. The techniques and processes related to biotechnology have been provided in this book. This book provides insights to the readers about the concept of biostatistics and software which are used for the analysis of the data while performing research.
Call Number: Available OnlineISBN: 9781774075081Publication Date: 2019
Background information on topics presented in the course
This guide is intended to assist you with the concepts presented in NUR 520: Epidemiological & Biostatistical Applications in Healthcare. Within this guide, you will find resources that explain research methods and sources of data that you will encounter in the medical field.
Instructor Videos in Course Announcements
|
Module/Topic |
Video |
|
Mod 1/p-value |
|
|
|
https://youtu.be/0-fEKHSeRR0?list=PLm9FYjKtq7Pzjh7e727hSr8VvSR9OvqsZ |
|
|
https://youtu.be/eyknGvncKLw?list=PLm9FYjKtq7Pzjh7e727hSr8VvSR9OvqsZ |
|
Mod 1/ Statistical tests |
|
|
|
|
|
|
|
|
Mod 1/Independent and Dependent Variables |
|
|
|
|
|
|
|
|
|
|
|
Mod 2/Confounding & Bias |
|
|
Mod 2/Reliability vs. Validity |
|
|
Mod 2/How to read Research articles |
|
|
|
|
|
|
|
|
Mod 3/Confidence Intervals |
|
|
|
|
|
Mod 4/p-value (again) |
|
|
|
|
|
Mod 4/Confounding, chance, & bias |
|
|
Mod 5/ Relative Risk & Odds Ratio |
|
|
|
|
|
Mod 5/ Prevalence & Incidence |
|
|
Mod 5/ P&I cont. |
|
|
|
|
|
|
|
|
Mod 6/Study designs |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Mod 7/Systems Thinking |
|
|
Mod 8/Hill’s criteria |
|
|
|
|
|
Mod 8/Generalizability |
|
|
|
|
|
Mod 9/Sample Size Calculation |