Research methodology-Epidemiology-Biostatistics
| Title | Ερευνητική μεθοδολογία, Επιδημιολογία, Βιοστατιστική / Research methodology-Epidemiology-Biostatistics |
| Code | GS04 |
| Faculty | Health Sciences |
| School | Dentistry |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Konstantinos Arapostathis |
| Common | No |
| Status | Active |
| Course ID | 600021067 |
Programme of Study: Metaptychiakó Prógramma Spoudṓn "Paidodontiatrikī" - 2024-2025+
Registered students: 6
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| KORMOS | Compulsory Course | 1 | 1 | 2 |
| Academic Year | 2025 – 2026 |
| Class Period | Winter |
| Faculty Instructors | |
| Class ID | 600287107
|
Course Type 2021
General Knowledge
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600287107
- At the Website of the School: https://dent.auth.gr/
Language of Instruction
- Greek (Instruction, Examination)
- English (Instruction, Examination)
Learning Outcomes
Although statistical software is not the means for understanding statistics, it plays a crucial role in any statistical analysis, so it will be used for the immediate application of theoretical knowledge as well as for all examples and problems during the semester while students will learn how to use it for dental research data analysis (IBM SPSS Statistics and R).
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
- Work in teams
- Design and manage projects
Course Content (Syllabus)
1. Evidence- based dentistry. Research hypothesis and study design. Variables, Sampling, Randomization, Blinding, the problem of missing data.
2. Experimental (Clinical trials) and observational studies in medical and dental research (CONSORT 2010 , STROBE 2007). An introduction to the IBM SPSS Statistics software. Data View and Variable View, the Output file, the Syntax file, Compute, Select, Recode and Weight commands. Introduction to the R Commander and to the open statistical platform jamovi.
3. An introduction to Probability. Random Variables and Distributions (Binomial, Poisson and Normal). Parameters and estimators, descriptive statistics.
4. Sampling Distributions. The Standard Normal Distribution, the Law of the Large Numbers, and the Central Limit Theorem, the t-distribution. Confidence Intervals, Hypothesis Testing, Type I and II errors, the Power of a Study and Sample Size calculation. P-value, Statistical and Clinical Significance. How to read an article.
5. Normality tests and the logarithmic transformation. The t-test for one and two independent samples and the non- parametric Mann Whitney U test.
6. The t-test for related samples and the non-parametric Wilcoxon test. Review exercises.
7. One-way analysis of variance. Welsh and Brown-Forsythe robust analysis of variance. The Kruskal Wallis non-parametric ANOVA. Pair wise comparisons and the Bonferroni adjustment for the Type I Error.
8. Nominal data, cross-sectional studies. The Binomial test, the Chi-Square test, the Fisher’s exact test. Calculation of the p-value using the Monte Carlo Method.
9. Nominal data and related groups. The McNemar test, the Marginal Homogeneity test (Stuart-Maxwell) and the Cochran’s Q test. Review exercises.
10. Statistical analysis of observational studies (Cohort and Case-Control studies). The Relative Risk (RR) and the Odds Ratios (OR). Diagnostic tests.
11. Association, Agreement and Reliability. Pearson’s correlation coefficient, Spearman's rank-order correlation coefficient, Cohen's kappa, intraclass correlation coefficient.
12. An introduction to Linear and Generalized Linear Model, Simple and Multiple Linear Regression, Logistic Regression.
13. Two-Way Analysis of Variance. An Introduction to the statistical analysis of repeated measurements and longitudinal data with Mixed Linear Models. The non-parametric Friedman’s test.
14. Review exercises.
Educational Material Types
- Notes
- Slide presentations
- Video lectures
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Seminars | 14 | ||||
| Internship | 10 | ||||
| Project | 16 | ||||
| Written assigments | 10 | ||||
| Exams | 2 | ||||
| Total | 52 |
Student Assessment
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Assignment (Formative)
- Written Exam with Problem Solving (Formative)
Bibliography
Additional bibliography for study
1991. Practical statistics for medical research. Douglas G. Altman.
1997. Critical thinking: understanding and evaluating dental research. Brunette D.M. Quintessense
2014. Medical Statistics- A Guide to SPSS, Data Analysis and Critical Appraisal. Peat Barton.
2017. Dental statistics made easy. Smeeton.
2018. Medical biostatistics. Indrayan, Malhotra.
2018. Principles of Biostatistics. Pagano, Gauvreau.
2000. Statistics with Confidence- Confidence Intervals and Statistical Guidelines. Altman_et al.
2008. How to Display Data. Freeman et al.
2014. How to Read a Paper- The Basics of Evidence-Based Medicine. Greenhalgh.
2003. How to write a paper. Hall.
2017. Using the R Commander. John Fox, Chapman & Hall/CRC Press
Last Update
06-01-2023
