TB011701 Exercise and Seminar on Epidemiological Research and It's Analysis

Hiroshima University Syllabus

Japanese

Academic Year 2025Year School/Graduate School Graduate School of Biomedical and Health Sciences (Master’s Course)

Lecture Code TB011701 Subject Classification Specialized Education

Subject Name 疫学調査分析演習

Subject Name
（Katakana）エキガクチョウサブンセキエンシュウ

Subject Name in
English Exercise and Seminar on Epidemiological Research and It's Analysis

Instructor FUKUMA SHINGO,KO KO,AKITA TOMOYUKI,SUGIYAMA AYA

Instructor
(Katakana) フクマ　シンゴ,コ　コ,アキタ　トモユキ,スギヤマ　アヤ

Campus Kasumi Semester/Term 2nd-Year,  First Semester,  First Semester

Days, Periods, and Classrooms (1st) Inte

Lesson Style Seminar Lesson Style
(More Details) Face-to-face

Practice in Data analysis
Lecture room: Seminar room No.2  (Apr 26: Lecture room 1)

Credits 2.0 Class Hours/Week 　 Language of Instruction B : Japanese／English

Course Level 5 : Graduate Basic

Course Area（Area） 27 : Health Sciences

Course Area（Discipline） 01 : Medical Sciences

Eligible Students Master’s course students

Keywords R, Epidemiology, Data analysis, Clinical epidemiology, Causal inference

Special Subject for Teacher Education 　 Special Subject 　

Class Status
within Educational
Program
(Applicable only to targeted subjects for undergraduate students) MPH program: "Epidemiology" in Council on Education for Public Health (CEPH) USA
Criterion referenced
Evaluation
(Applicable only to targeted subjects for undergraduate students)

Class Objectives
/Class Outline Acquire methods of analyzing epidemiological survey data using statistical software R.

Class Schedule Part 1. Basic Statistical analysis using R
Lesson 1-3. (April 12, 10:30-12:00, 12:50-14:20, 14:35-16:05)  Descriptive statistics and Univariable analysis
Lesson 4-6.（April 26, 10:30-12:00, 12:50-14:20, 14:35-16:05） Data handling, missing data imputation, Survival analysis ※Lecture room 1
Lesson 7-8. (May 10, 12:50-14:20, 14:35-16:05)  Multivariate analysis

Part 2.  Statistical analysis in Causal Inference
Lesson 9-10（June 21, 10:30-12:00, 12:50-14:20）Propensity score
Lesson 11-12（July 5, 10:30-12:00, 12:50-14:20）Regression Discontinuity Design (RDD), instrumental variable method (IV)
Lesson 13-15（July 26, 10:30-12:00, 12:50-14:20, 14:35-16:05） Workshop (Group work, presentation)

Text/Reference
Books,etc. Handout

PC or AV used in
Class,etc. Handouts

(More Details) Slide

Learning techniques to be incorporated Discussions, Paired Reading, Quizzes/ Quiz format, PBL (Problem-based Learning)/ TBL (Team-based Learning), Project Learning, Post-class Report

Suggestions on
Preparation and
Review (1st - 15th)
Students should review the distributed materials after each class.
This lecture is intended for students with basic knowledge of biostatistics and experience in analysis with GUI statistical software such as JMP and SPSS, and the goal is for them to master analytical methods in R.
In the first part of the course, students will learn how to use statistical functions in R to analyze the analytical methods they have learned in the previous biostatistics lectures. Students are encouraged to review the previous lectures and understand the input/output of statistical functions in R.
In the middle part of the course, you will learn how to implement analyses used in clinical epidemiological studies and causal inference using R. In the last part of the course, you will learn how to distribute the data into groups.
In the last part of the course, data will be distributed to each group, and students will analyze and summarize the data through group work.

Requirements Completion of either
"Basic Biostatistics and Basic Clinical Statistics",
"Basic and Advanced Training on Methodology for Clinical Research",
"Exercises and Seminar on Medical Statistics Using Statistical Software"
is required.
Please have R and RStudio installed by the start of the lecture.

Grading Method Status of class work, reports for each class, and final presentation

Practical Experience

Summary of Practical Experience and Class Contents based on it

Message

Other Language
Handout of all lecture: Japanese and/or English (Depend on student)
Explanation of all lecture: Japanese and/or English (Depend on student)

Please fill in the class improvement questionnaire which is carried out on all classes.
Instructors will reflect on your feedback and utilize the information for improving their teaching.

Academic Year	2025Year	School/Graduate School	Graduate School of Biomedical and Health Sciences (Master’s Course)
Lecture Code	TB011701	Subject Classification	Specialized Education
Subject Name	疫学調査分析演習
Subject Name （Katakana）	エキガクチョウサブンセキエンシュウ
Subject Name in English	Exercise and Seminar on Epidemiological Research and It's Analysis
Instructor	FUKUMA SHINGO,KO KO,AKITA TOMOYUKI,SUGIYAMA AYA
Instructor (Katakana)	フクマ　シンゴ,コ　コ,アキタ　トモユキ,スギヤマ　アヤ
Campus	Kasumi	Semester/Term	2nd-Year, First Semester, First Semester
Days, Periods, and Classrooms	(1st) Inte
Lesson Style	Seminar	Lesson Style (More Details)	Face-to-face
Practice in Data analysis Lecture room: Seminar room No.2 (Apr 26: Lecture room 1)
Credits	2.0	Class Hours/Week		Language of Instruction	B : Japanese／English
Course Level	5 : Graduate Basic
Course Area（Area）	27 : Health Sciences
Course Area（Discipline）	01 : Medical Sciences
Eligible Students	Master’s course students
Keywords	R, Epidemiology, Data analysis, Clinical epidemiology, Causal inference
Special Subject for Teacher Education		Special Subject
Class Status within Educational Program (Applicable only to targeted subjects for undergraduate students)	MPH program: "Epidemiology" in Council on Education for Public Health (CEPH) USA
Criterion referenced Evaluation (Applicable only to targeted subjects for undergraduate students)
Class Objectives /Class Outline	Acquire methods of analyzing epidemiological survey data using statistical software R.
Class Schedule	Part 1. Basic Statistical analysis using R Lesson 1-3. (April 12, 10:30-12:00, 12:50-14:20, 14:35-16:05) Descriptive statistics and Univariable analysis Lesson 4-6.（April 26, 10:30-12:00, 12:50-14:20, 14:35-16:05） Data handling, missing data imputation, Survival analysis ※Lecture room 1 Lesson 7-8. (May 10, 12:50-14:20, 14:35-16:05) Multivariate analysis Part 2. Statistical analysis in Causal Inference Lesson 9-10（June 21, 10:30-12:00, 12:50-14:20）Propensity score Lesson 11-12（July 5, 10:30-12:00, 12:50-14:20）Regression Discontinuity Design (RDD), instrumental variable method (IV) Lesson 13-15（July 26, 10:30-12:00, 12:50-14:20, 14:35-16:05） Workshop (Group work, presentation)
Text/Reference Books,etc.	Handout
PC or AV used in Class,etc.	Handouts
(More Details)	Slide
Learning techniques to be incorporated	Discussions, Paired Reading, Quizzes/ Quiz format, PBL (Problem-based Learning)/ TBL (Team-based Learning), Project Learning, Post-class Report
Suggestions on Preparation and Review	(1st - 15th) Students should review the distributed materials after each class. This lecture is intended for students with basic knowledge of biostatistics and experience in analysis with GUI statistical software such as JMP and SPSS, and the goal is for them to master analytical methods in R. In the first part of the course, students will learn how to use statistical functions in R to analyze the analytical methods they have learned in the previous biostatistics lectures. Students are encouraged to review the previous lectures and understand the input/output of statistical functions in R. In the middle part of the course, you will learn how to implement analyses used in clinical epidemiological studies and causal inference using R. In the last part of the course, you will learn how to distribute the data into groups. In the last part of the course, data will be distributed to each group, and students will analyze and summarize the data through group work.
Requirements	Completion of either "Basic Biostatistics and Basic Clinical Statistics", "Basic and Advanced Training on Methodology for Clinical Research", "Exercises and Seminar on Medical Statistics Using Statistical Software" is required. Please have R and RStudio installed by the start of the lecture.
Grading Method	Status of class work, reports for each class, and final presentation
Practical Experience
Summary of Practical Experience and Class Contents based on it
Message
Other	Language Handout of all lecture: Japanese and/or English (Depend on student) Explanation of all lecture: Japanese and/or English (Depend on student)
Please fill in the class improvement questionnaire which is carried out on all classes. Instructors will reflect on your feedback and utilize the information for improving their teaching.

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