Statistics for Health Care Professionals

Statistics for Health Care Professionals
Author: Ian Scott
Publisher: SAGE
Total Pages: 252
Release: 2005-02-09
Genre: Mathematics
ISBN: 9780761974765

Focusing on quantative approaches to investigating problems, this title introduces the basics rules and principles of statistics, encouraging the reader to think critically about data analysis and research design, and how these factors can impact upon evidence-based practice.

Munro's Statistical Methods for Health Care Research

Munro's Statistical Methods for Health Care Research
Author: Stacey Beth Plichta
Publisher: Lippincott Williams & Wilkins
Total Pages: 567
Release: 2012
Genre: Medical
ISBN: 9781451115611

This work provides a foundation in the statistics portion of nursing. Topics expanded in this edition include reliability analysis, path analysis, measurement error, missing data, and survival analysis.

Statistical Methods for Health Care Research

Statistical Methods for Health Care Research
Author: Barbara Hazard Munro
Publisher: Lippincott Raven
Total Pages: 484
Release: 2001
Genre: Business & Economics
ISBN:

This singular text provides nursing students as well as students in all other health-related disciplines with a solid foundation for understanding data and specific statistical techniques. In this newest edition, outstanding faculty contributors focus on the most current and most frequently used statistical methods in today's health care literature, covering essential material for a variety of program levels including in-depth courses beyond the basic statistics course. Well-organized and clear text discussions and great learning tools help you cut through the complexities and fully comprehend the concepts of this often intimidating area of study. Book jacket.

Statistical Methods in Healthcare

Statistical Methods in Healthcare
Author: Frederick W. Faltin
Publisher: John Wiley & Sons
Total Pages: 533
Release: 2012-07-24
Genre: Medical
ISBN: 1119942047

Statistical Methods in Healthcare In recent years the number of innovative medicinal products and devices submitted and approved by regulatory bodies has declined dramatically. The medical product development process is no longer able to keep pace with increasing technologies, science and innovations and the goal is to develop new scientific and technical tools and to make product development processes more efficient and effective. Statistical Methods in Healthcare focuses on the application of statistical methodologies to evaluate promising alternatives and to optimize the performance and demonstrate the effectiveness of those that warrant pursuit is critical to success. Statistical methods used in planning, delivering and monitoring health care, as well as selected statistical aspects of the development and/or production of pharmaceuticals and medical devices are also addressed. With a focus on finding solutions to these challenges, this book: Provides a comprehensive, in-depth treatment of statistical methods in healthcare, along with a reference source for practitioners and specialists in health care and drug development. Offers a broad coverage of standards and established methods through leading edge techniques. Uses an integrated case study based approach, with focus on applications. Looks at the use of analytical and monitoring schemes to evaluate therapeutic performance. Features the application of modern quality management systems to clinical practice, and to pharmaceutical development and production processes. Addresses the use of modern statistical methods such as Adaptive Design, Seamless Design, Data Mining, Bayesian networks and Bootstrapping that can be applied to support the challenging new vision. Practitioners in healthcare-related professions, ranging from clinical trials to care delivery to medical device design, as well as statistical researchers in the field, will benefit from this book.

Beyond the HIPAA Privacy Rule

Beyond the HIPAA Privacy Rule
Author: Institute of Medicine
Publisher: National Academies Press
Total Pages: 334
Release: 2009-03-24
Genre: Computers
ISBN: 0309124999

In the realm of health care, privacy protections are needed to preserve patients' dignity and prevent possible harms. Ten years ago, to address these concerns as well as set guidelines for ethical health research, Congress called for a set of federal standards now known as the HIPAA Privacy Rule. In its 2009 report, Beyond the HIPAA Privacy Rule: Enhancing Privacy, Improving Health Through Research, the Institute of Medicine's Committee on Health Research and the Privacy of Health Information concludes that the HIPAA Privacy Rule does not protect privacy as well as it should, and that it impedes important health research.

Practical Statistics for Medical Research

Practical Statistics for Medical Research
Author: Douglas G. Altman
Publisher: CRC Press
Total Pages: 624
Release: 1990-11-22
Genre: Mathematics
ISBN: 1000228819

Practical Statistics for Medical Research is a problem-based text for medical researchers, medical students, and others in the medical arena who need to use statistics but have no specialized mathematics background. The author draws on twenty years of experience as a consulting medical statistician to provide clear explanations to key statistical concepts, with a firm emphasis on practical aspects of designing and analyzing medical research. Using real data and including dozens of interesting data sets, this bestselling text gives special attention to the presentation and interpretation of results and the many real problems that arise in medical research.

Brief Guidelines for Methods and Statistics in Medical Research

Brief Guidelines for Methods and Statistics in Medical Research
Author: Jamalludin Bin Ab Rahman
Publisher: Springer
Total Pages: 114
Release: 2015-10-14
Genre: Medical
ISBN: 9812879250

This book serves as a practical guide to methods and statistics in medical research. It includes step-by-step instructions on using SPSS software for statistical analysis, as well as relevant examples to help those readers who are new to research in health and medical fields. Simple texts and diagrams are provided to help explain the concepts covered, and print screens for the statistical steps and the SPSS outputs are provided, together with interpretations and examples of how to report on findings. Brief Guidelines for Methods and Statistics in Medical Research offers a valuable quick reference guide for healthcare students and practitioners conducting research in health related fields, written in an accessible style.

Nonparametric Statistics for Health Care Research

Nonparametric Statistics for Health Care Research
Author: Marjorie A. Pett
Publisher: SAGE Publications
Total Pages: 392
Release: 2015-06-29
Genre: Social Science
ISBN: 1483324524

What do you do when you realize that the data set from the study that you have just completed violates the sample size or other requirements needed to apply parametric statistics? Nonparametric Statistics for Health Care Research was developed for such scenarios—research undertaken with limited funds, often using a small sample size, with the primary objective of improving client care and obtaining better client outcomes. Covering the most commonly used nonparametric statistical techniques available in statistical packages and on open-resource statistical websites, this well-organized and accessible Second Edition helps readers, including those beyond the health sciences field, to understand when to use a particular nonparametric statistic, how to generate and interpret the resulting computer printouts, and how to present the results in table and text format.

Individual Participant Data Meta-Analysis

Individual Participant Data Meta-Analysis
Author: Richard D. Riley
Publisher: John Wiley & Sons
Total Pages: 38
Release: 2021-06-08
Genre: Medical
ISBN: 1119333725

Individual Participant Data Meta-Analysis: A Handbook for Healthcare Research provides a comprehensive introduction to the fundamental principles and methods that healthcare researchers need when considering, conducting or using individual participant data (IPD) meta-analysis projects. Written and edited by researchers with substantial experience in the field, the book details key concepts and practical guidance for each stage of an IPD meta-analysis project, alongside illustrated examples and summary learning points. Split into five parts, the book chapters take the reader through the journey from initiating and planning IPD projects to obtaining, checking, and meta-analysing IPD, and appraising and reporting findings. The book initially focuses on the synthesis of IPD from randomised trials to evaluate treatment effects, including the evaluation of participant-level effect modifiers (treatment-covariate interactions). Detailed extension is then made to specialist topics such as diagnostic test accuracy, prognostic factors, risk prediction models, and advanced statistical topics such as multivariate and network meta-analysis, power calculations, and missing data. Intended for a broad audience, the book will enable the reader to: Understand the advantages of the IPD approach and decide when it is needed over a conventional systematic review Recognise the scope, resources and challenges of IPD meta-analysis projects Appreciate the importance of a multi-disciplinary project team and close collaboration with the original study investigators Understand how to obtain, check, manage and harmonise IPD from multiple studies Examine risk of bias (quality) of IPD and minimise potential biases throughout the project Understand fundamental statistical methods for IPD meta-analysis, including two-stage and one-stage approaches (and their differences), and statistical software to implement them Clearly report and disseminate IPD meta-analyses to inform policy, practice and future research Critically appraise existing IPD meta-analysis projects Address specialist topics such as effect modification, multiple correlated outcomes, multiple treatment comparisons, non-linear relationships, test accuracy at multiple thresholds, multiple imputation, and developing and validating clinical prediction models Detailed examples and case studies are provided throughout.