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Routledge International Handbook of Advanced Quantitative Methods in Nursing Research

Editat de Susan J Henly
en Limba Engleză Paperback – 29 iun 2017
Designed to support global development of nursing science, the Routledge International Handbook of Advanced Quantitative Methods in Nursing Research provides a new, comprehensive, and authoritative treatment of advanced quantitative methods for nursing research.
Incorporating past approaches that have served as the foundation for the science, this cutting edge book also explores emerging approaches that will shape its future. Divided into six parts, it covers:
-the domain of nursing science
- measurement—classical test theory, IRT, clinimetrics, behavioral observation, biophysical measurement
-models for prediction and explanation—SEM, general growth mixture models, hierarchical models, analysis of dynamic systems
-intervention research—theory-based interventions, causality, third variables, pilot studies, quasi-experimental design, joint models for longitudinal data and time to event
-e-science—DIKW paradigm, big data, data mining, omics, FMRI
-special topics—comparative effectiveness and meta-analysis, patient safety, economics research in nursing, mixed methods, global research dissemination
Written by a distinguished group of international nursing scientists, scientists from related fields, and methodologists, the Handbook is the ideal reference for everyone involved in nursing science, whether they are graduate students, academics, editors and reviewers, or clinical investigators.
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Specificații

ISBN-13: 9781138552852
ISBN-10: 1138552852
Pagini: 464
Dimensiuni: 174 x 246 x 39 mm
Greutate: 0.76 kg
Ediția:1
Editura: Taylor & Francis
Colecția Routledge
Locul publicării:Oxford, United Kingdom

Public țintă

Postgraduate and Undergraduate

Cuprins

Part 1: The Domain of Nursing Science  1. The Domain of Nursing Science  2. Theorising in Nursing Science  Part 2: Measurement  3. Classical Test Theory  4. Clinimetrics  5. Item Response Theory: A Statistical Theory of Measurement Based on Fungible Items  6. Behavioral Observation  7. Biophysical Observation  Part 3: Prediction and Explanation  8. Structural Equation Modeling  9. General Growth Mixture Models  10. Multilevel Models  11. Analysis of Dynamic Systems: The Modeling of Change and Variability  Part 4: Experimental and Quasi-experimental Design  12. Theory-based Nursing Interventions  13. Pilot Studies for Randomized Clinical Trials  14. Causality in Experiments and Observational Studies  15. Quasi-experimental Design in Nursing Research  16. Third Variables: Scientific Meanings and Modeling in Non-randomized Studies  17. Joint Models for Longitudinal Data and Time-to-event Occurrence  Part 5: E-science Methods  18. Data, Information, Knowledge, Wisdom  19. Big Data in Nursing Research  20. Data Mining and Data Visualization  21. Genomic, Transcriptomic, Epigenomic, and Proteomic Approaches  22. A Survey of Sources of Noise in FMRI  Part 6: Applications and Special Topics  23. Comparative Effectiveness Research and Meta-analysis  24. Patient Safety Research: Methodological Challenges  25. Economic Evaluations for Nursing Research  26. Mixed Methods  27. Global Generation and Dissemination of Nursing Science

Notă biografică

Dr. Susan J. Henly is Professor Emerita, University of Minnesota, School of Nursing, Minneapolis, Minnesota, USA. She earned her BS with a major in nursing from the College of St. Teresa, Winona, Minnesota and practiced in rural acute care, perinatal nursing, and neonatal intensive care in Alaska, New Mexico and Minnesota before returning to graduate school. Her MS degree in nursing, focused on perinatal health research, is from the University of Minnesota, Twin Cities. She earned her PhD in psychometric methods from the University of Minnesota, Twin Cities. She served on the College of Nursing faculty at the University of North Dakota, Grand Forks prior to her appointment at Minnesota.
Over the past 30 years, Sue’s research has focused on psychmetric methods for nursing research with special interests in robustness of estimators in the analysis of covariance structures, model selection, and longitudinal models for health trajectories. She was Methods Director for the National Institute of Nursing Research-funded Center for Health Trajectory Research at the University of Minnesota, School of Nursing. Sue has a special interest in advancing quantitative methods in nursing PhD programs. She was director of the American Indian MS to PhD Nursing Science Bridge Program (funded by the National Institute of General Medical Sciences) and chaired the Council for the Advancement of Nursing Sciences Idea Festival for Nursing Science Education. She has extensive service as a peer reviewer for nursing science, related fields, and methodology journals and has contributed to the peer review literature. Sue is Editor of Nursing Research. She is a member of the Japan Academy of Nursing Science and the American Academy of Nursing.

Descriere

Designed to support global development of nursing science, this Handbook provides a new, comprehensive, and authoritative treatment of advanced quantitative methods for nursing research. Incorporating past approaches that have served as the foundation for the science, it also explores emerging approaches that will shape its future.