Objectives and competences
• Use methods of predictive modeling to solve problems in healthcare.
• Evaluate the applicability of predictive models in healthcare.
• Learn principles of advanced data management and analysis.
• Evaluate potential of open datasets for secondary data analysis using predictive modeling in healthcare.
Content (Syllabus outline)
- Exploratory data analysis
- Bivariate statistical tests
- Multivariate statistical tests
- Statistical methods for predictive modeling
- Validation and Evaluation of derived predictive models
- Advanced predictive modeling using machine learning techniques
- Practical examples from diffferent fields of healthcare
Learning and teaching methods
Lectures, seminars
Intended learning outcomes - knowledge and understanding
Students:
• Will know how to use predictive models to solve problems in healthcare.
• Will be able to use appropriate graphical data representations.
• Will be able to identify different situations where predictive modeling could be used.
• Gained knowledge will be routinely used in the student's future work.
• Experience gathered here will be aplicable to actual real-world problems in healthcare.
Readings
Obvezna/Mandatory
IBM, 2024. IBM SPSS Regression 29. Available at: https://www.ibm.com/docs/en/SSLVMB_29.0.0/pdf/IBM_SPSS_Regression.pdf
GOSAK, Lucija, CILAR BUDLER, Leona, WATSON, Roger and ŠTIGLIC, Gregor, 2024, Advanced Quantitative Research Methods in Nursing [online]. 2024. Maribor : University of Maribor, University Press. [Accessed 20 August 2024]. ISBN 978-961-286-888-8. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=89527
Priporočena/Recommended:
Domače in mednarodne strokovne in znanstvene publikacije s področja učne enote.
Prerequisits
Fundamental content knowledge from the courses’ field
