Nursing Research Using Data Analysis

Author: Mary De Chesnay, PhD, RN, PMHCNS-BC, FAAN
Publisher: Springer Publishing Company
ISBN: 0826126898
Size: 35.11 MB
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This is a concise, step-by-step guide to conducting qualitative nursing research using various forms of data analysis. It is part of a unique series of books devoted to seven different qualitative designs and methods in nursing, written for both novice researchers and specialists seeking to develop or expand their competency. This practical resource encompasses such methodologies as content analysis, a means of organizing and interpreting data to elicit themes and concepts; discourse analysis, used to analyze language to understand social or historical context; narrative analysis, in which the researcher seeks to understand human experience through participant stories; and focus groups and case studies, used to understand the consensus of a group or the experience of an individual and his or her reaction to a difficult situation such as disease or trauma. Written by a noted qualitative research scholar and contributing experts, the book describes the philosophical basis for conducting research using data analysis and delivers an in-depth plan for applying its methodologies to a particular study, including appropriate methods, ethical considerations, and potential challenges. It presents practical strategies for solving problems related to the conduct of research using the various forms of data analysis and presents a rich array of case examples from published nursing research. These include author analyses to support readers in decision making regarding their own projects. The book embraces such varied topics as data security in qualitative research, the image of nursing in science fiction literature, the trajectory of research in several nursing studies throughout Africa, and many others. Focused on the needs of both novice researchers and specialists, it will be of value to health institution research divisions, in-service educators and students, and graduate nursing educators and students. Key Features: Explains how to conduct nursing research using content analysis, discourse analysis, narrative analysis, and focus groups and case studies Presents state-of-the-art designs and protocols Focuses on solving practical problems related to the conduct of research Features rich nursing exemplars in a variety of health/mental health clinical settings in the United States and internationally

Statistics And Data Analysis For Nursing Research

Author: Denise F. Polit
Publisher: Prentice Hall
ISBN: 9780135085073
Size: 31.52 MB
Format: PDF, ePub
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The second edition of Statistics and Data Analysis for Nursing , uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Readers are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. Special focus is given to quantitative methods. Other features include management of data, how to "clean" data, and how to work around missing data. New to this edition are updated research examples utilizinging examples from an international mix of studies published by nurse researchers in 2006-2009.

Nursing Research Using Historical Methods

Author: Mary De Chesnay
Publisher: Springer Publishing Company
ISBN: 0826126170
Size: 51.83 MB
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Nursing Research Using Historical Methods: Qualitative Designs and Methods in Nursing is one book in a series of seven volumes that presents concise, how-to guides to conducting qualitative research -- for novice researchers and specialists seeking to develop or expand their competency, health institution research divisions, in-service educators and students, and graduate nursing educators and students.

Data Analysis Statistics For Nursing Research

Author: Denise F. Polit
Publisher: Prentice Hall
ISBN: 9780838563298
Size: 18.10 MB
Format: PDF, ePub, Mobi
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This introductory textbook uses a conversational style to teach students how to use statistical methods and procedures for the analysis of research findings. Students are guided through the process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to clean data, and how to work around missing data, is discussed.

Design And Analysis Of Clinical Nursing Research Studies

Author: Colin R Martin
Publisher: Routledge
ISBN: 1134589719
Size: 47.65 MB
Format: PDF, Kindle
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This invaluable text on the design and analysis of clinical research studies explains the basis of experimental design and statistics in a way that is sensitive to the clinical context in which nurses work. It uses data from actual studies to illustrate how to: *design the study *use and select data *present research findings *use a computer for statistical analysis. The scope of the study designs and associated statistical techniques covered in the book allow both the beginning nurse researcher and the more seasoned professional nurse investigator to approach a research study with confidence and optimism. The authors show how qualitative data can be approached quantitatively, what the advantages of this are from the nursing viewpoint, and how quantitative methodology can help nurses to develop a common research language with other disciplines involved in patient care.

Big Data Enabled Nursing

Author: Connie W. Delaney
Publisher: Springer
ISBN: 3319533002
Size: 21.48 MB
Format: PDF, ePub
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Historically, nursing, in all of its missions of research/scholarship, education and practice, has not had access to large patient databases. Nursing consequently adopted qualitative methodologies with small sample sizes, clinical trials and lab research. Historically, large data methods were limited to traditional biostatical analyses. In the United States, large payer data has been amassed and structures/organizations have been created to welcome scientists to explore these large data to advance knowledge discovery. Health systems electronic health records (EHRs) have now matured to generate massive databases with longitudinal trending. This text reflects how the learning health system infrastructure is maturing, and being advanced by health information exchanges (HIEs) with multiple organizations blending their data, or enabling distributed computing. It educates the readers on the evolution of knowledge discovery methods that span qualitative as well as quantitative data mining, including the expanse of data visualization capacities, are enabling sophisticated discovery. New opportunities for nursing and call for new skills in research methodologies are being further enabled by new partnerships spanning all sectors.

Nursing Research Using Grounded Theory

Author: Mary De Chesnay, PhD, RN, PMHCNS-BC, FAAN
Publisher: Springer Publishing Company
ISBN: 0826134688
Size: 19.69 MB
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Grounded theory, often considered the parent of all qualitative research, is a complex approach used to develop theory about a phenomenon rooted in observation of empirical data. Widely used in nursing, grounded theory enables researchers to apply what they learn from interviewees to a wider client population. This is a practical "how to" guide to conducting research using this qualitative design. It is part of an innovative series for novice researchers and specialists alike focusing on nine state-of-the-art methodologies from a nursing perspective. International scholars of grounded theory discuss the theoretical rationale for using this design, describe its components, and delineate a plan for generating theory using grounded theory methodology. Examples from published nursing research, with author commentary, help support new and experienced researchers in making decisions and facing challenges. The book describes traditional and focused grounded theory, phases of research, and methodology from sample and setting to dissemination and follow-up. It encompasses state-of-the-art research about grounded theory with an extensive bibliography and resources. Varied case studies range from promoting health for an overweight child to psychological adjustment of Chinese women with breast cancer to a study of nursing students' experiences in the off-campus clinical setting, among many others. The book also discusses techniques whereby researchers can ensure high standards of rigor. Each chapter includes objectives, competencies, review questions, critical thinking exercises, and links to web resources. With a focus on practical problem solving throughout, the book will be of value to novice and experienced nurse researchers, graduate teachers and students, in-service educators and students, and nursing research staff at health care institutions. Key Features: Includes examples of state-of-the-art grounded theory nursing research with content analysis and extensive bibliography Describes types of grounded theory, phases of research, and methodology Provides case studies including description, data collection and analysis, and dissemination Written by international scholars of grounded theory research

Statistics And Data Analysis For Nursing Research

Author: CTI Reviews
Publisher: Cram101 Textbook Reviews
ISBN: 1538817675
Size: 18.67 MB
Format: PDF, ePub
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Facts101 is your complete guide to Statistics and Data Analysis for Nursing Research. In this book, you will learn topics such as Central Tendency, Variability, and Relative Standing, Bivariate Description: Crosstabulation, Risk Indexes, and Correlation, Statistical inference, and t Tests: Testing Two Mean Differences plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.

Statistics And Data Analysis For Nursing Research Pearson New International Edition

Author: Denise F. Polit
Publisher: Pearson Higher Ed
ISBN: 1292054921
Size: 48.10 MB
Format: PDF, ePub, Docs
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The second edition of Statistics and Data Analysis for Nursing, uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.

Introduction To Research Methods And Data Analysis In The Health Sciences

Author: Gareth Hagger-Johnson
Publisher: Routledge
ISBN: 1317674413
Size: 54.30 MB
Format: PDF, ePub
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Whilst the ‘health sciences’ are a broad and diverse area, and includes public health, primary care, health psychology, psychiatry and epidemiology, the research methods and data analysis skills required to analyse them are very similar. Moreover, the ability to appraise and conduct research is emphasised within the health sciences – and students are expected increasingly to do both. Introduction to Research Methods and Data Analysis in the Health Sciences presents a balanced blend of quantitative research methods, and the most widely used techniques for collecting and analysing data in the health sciences. Highly practical in nature, the book guides you, step-by-step, through the research process, and covers both the consumption and the production of research and data analysis. Divided into the three strands that run throughout quantitative health science research – critical numbers, critical appraisal of existing research, and conducting new research – this accessible textbook introduces: Descriptive statistics Measures of association for categorical and continuous outcomes Confounding, effect modification, mediation and causal inference Critical appraisal Searching the literature Randomised controlled trials Cohort studies Case-control studies Research ethics and data management Dissemination and publication Linear regression for continuous outcomes Logistic regression for categorical outcomes. A dedicated companion website offers additional teaching and learning resources for students and lecturers, including screenshots, R programming code, and extensive self-assessment material linked to the book’s exercises and activities. Clear and accessible with a comprehensive coverage to equip the reader with an understanding of the research process and the practical skills they need to collect and analyse data, it is essential reading for all undergraduate and postgraduate students in the health and medical sciences.