Buch, Englisch, 464 Seiten, Format (B × H): 175 mm x 249 mm, Gewicht: 953 g
Buch, Englisch, 464 Seiten, Format (B × H): 175 mm x 249 mm, Gewicht: 953 g
ISBN: 978-0-415-52180-2
Verlag: Taylor & Francis
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.
Zielgruppe
Postgraduate and Undergraduate
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
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