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Information
| Unit | INSTITUTE OF MEDICAL SCIENCES |
| BIOSTATISTICS (MEDICINE) (MASTER) (WITHOUT THESIS) (EVENING EDUCATION) | |
| Code | BIST522 |
| Name | Multiple Regression and Modeling |
| Term | 2025-2026 Academic Year |
| Term | Spring |
| Duration (T+A) | 3-2 (T-A) (17 Week) |
| ECTS | 7 ECTS |
| National Credit | 4 National Credit |
| Teaching Language | Türkçe |
| Level | Lisansüstü Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Doç. Dr. İLKER ÜNAL |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
The aim of this course is to enable students to build multiple regression models for health-specific data, correctly interpret model results from statistical and clinical perspectives, and evaluate relationships between variables in an evidence-based manner.
Course Content
This course covers multiple regression and statistical modeling approaches used in health sciences. Topics include multiple linear regression, logistic regression for binary outcomes, model-building strategies, variable selection, interaction terms, confounding, model assumptions, multicollinearity, goodness-of-fit measures, and interpretation of results within clinical and epidemiological contexts. Applications are conducted using real health-related datasets.
Course Precondition
No prerequisites. (Completion of Basic Concepts in Biostatistics and Biostatistics Using Software Packages is recommended.)
Resources
Hosmer, D. W., Lemeshow, S. Applied Logistic Regression Kleinbaum, D. G., Kupper, L. L., Muller, K. E. Applied Regression Analysis and Other Multivariable Methods
Notes
Recent clinical and epidemiological regression studies
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Explain the purpose of multiple regression models in health sciences. |
| LO02 | Select appropriate regression models for continuous and binary health outcomes. |
| LO03 | Assess confounding and interaction effects during model building. |
| LO04 | Test model assumptions. |
| LO05 | Evaluate model fit and performance using appropriate measures. |
| LO06 | Interpret regression results within clinical and epidemiological contexts. |
| LO07 | Present model results in accordance with scientific reporting standards. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain basic biostatistics, probability, and demographic concepts used in health sciences. | 2 |
| PLO02 | Bilgi - Kuramsal, Olgusal | Define research designs, sampling methods, and data types used in health research. | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Explain the foundations of statistical approaches used in healthcare decision-making processes. | 2 |
| PLO04 | Bilgi - Kuramsal, Olgusal | Explain the basic logic of regression, modeling, and advanced statistical methods used in health sciences. | 5 |
| PLO05 | Beceriler - Bilişsel, Uygulamalı | Analyze and interpret data obtained from health research using appropriate statistical methods. | 5 |
| PLO06 | Beceriler - Bilişsel, Uygulamalı | Perform statistical analyses and generate outputs using statistical software packages. | 3 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Apply basic data science, artificial intelligence, and machine learning applications in health sciences. | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Evaluate multiple regression and survival analysis results in a clinical context. | 4 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Analyze genetic and biomedical data using basic analytical approaches. | |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Apply scale development, validity, and reliability analyses. | |
| PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Conduct data analysis and reporting within the scope of a term project. | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Apply and manage sampling procedures in health studies. | |
| PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Critically evaluate scientific studies from a statistical perspective. | 3 |
| PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Present analysis results in accordance with ethical principles. | 2 |
| PLO15 | Yetkinlikler - Alana Özgü Yetkinlik | Applies fundamental concepts of epidemiology and health statistics to clinical and field settings. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Course introduction; overview of multiple regression | Reading | Öğretim Yöntemleri: Anlatım |
| 2 | Regression logic in health data | Reading | Öğretim Yöntemleri: Anlatım |
| 3 | Multiple linear regression | Reading | Öğretim Yöntemleri: Anlatım |
| 4 | Variable selection and model building | Reading | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
| 5 | Introduction to logistic regression | Reading | Öğretim Yöntemleri: Anlatım |
| 6 | Interpretation of logistic regression | Reading | Öğretim Yöntemleri: Anlatım |
| 7 | Confounding and interaction effects | Reading | Öğretim Yöntemleri: Anlatım |
| 8 | Mid-Term Exam | Ölçme Yöntemleri: Sözlü Sınav |
|
| 9 | Model assumptions | Reading | Öğretim Yöntemleri: Anlatım |
| 10 | Multicollinearity | Reading | Öğretim Yöntemleri: Anlatım |
| 11 | Goodness-of-fit measures | Reading | Öğretim Yöntemleri: Anlatım |
| 12 | Clinical and epidemiological applications | Reading | Öğretim Yöntemleri: Alıştırma ve Uygulama, Anlatım |
| 13 | Reporting regression results | Reading | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
| 14 | General review and application I | Reading | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 15 | General review and application II | Reading | Öğretim Yöntemleri: Alıştırma ve Uygulama |
| 16 | Term Exams | Ölçme Yöntemleri: Ödev |
|
| 17 | Term Exams | Ölçme Yöntemleri: Ödev |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 5 | 70 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 1 | 15 | 15 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 15 | 15 |
| Total Workload (Hour) | 185 | ||
| Total Workload / 25 (h) | 7,40 | ||
| ECTS | 7 ECTS | ||