Numbering Code	G-MED26 7D006 GJ88	Year/Term	2022 ・ Year-round
Number of Credits	4	Course Type	research
Target Year	1st to 3rd year doctoral students	Target Student
Language	Japanese	Day/Period
Instructor name	SAWAMOTO NOBUKATSU (Graduate School of Medicine Professor) ISHIZU KOUICHI (Graduate School of Medicine Associate Professor)
Outline and Purpose of the Course	We aim to make students capable of independently identifying research topics based on clinical issues, planning and implementing methods to solve these issues, and critically interpreting the results obtained.
Course Goals	・Read original papers and make critical and constructive proposals to address issues relevant to the area of study, the methods to be adopted to solve these issues, and the process of interpreting results. ・Deepen your knowledge of research design, biostatistics, and research ethics guidelines to understand original clinical research papers and create your own research plans. ・Set your own topics based on clinical problems, plan and carry out research, and interpret the results critically.
Schedule and Contents	Session 1. Orientation Session 2. Research design 1 Session 3. Research design 2 Session 4. Statistical estimation Session 5. Comparison between two sample means and multiple group means Session 6. Linear regression and multiple regression analysis Session 7. Covariance analysis Session 8. Extending linear regression: Logistic regression Session 9. Time series analysis Session 10. Non-parametric tests Session 12. Indicators of relevance in non-parametric statistics Session 13. Multivariate analysis of variance Session 14. Discriminant analysis Session 15. Exploratory factor analysis Session 16. Path analysis and structural equation models Session 17. Cluster analysis Session 18. Canonical correlation analysis Session 19. Graphing and data processing with missing values Session 20. Research plan Session 21. Ethics 1 Session 22. Ethics 2 Sessions 23-30. Literature review Feedback is given through questions, etc.
Evaluation Methods and Policy	Comprehensive assessment based on the contents of presentations.
Course Requirements	Must have studied statistics to a sufficient level.
Study outside of Class (preparation and review)	As PhD students, we especially value independence, and expect that you will engage in independent study to delve deeper into your areas of research.
Textbooks	Textbooks/References	Not used
References, etc.	Introduced during class