COURSE INTRODUCTION AND APPLICATION INFORMATION

Course Name
Data Analyses for Repeated Measures
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
PSY 608
Fall/Spring
3
0
3
7.5
Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Third Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator -
Course Lecturer(s)
Assistant(s) -
Course Objectives This course will focus on the different statistical techniques used for repeated measures. This course provides an introduction to methods for analyzing repeated continuous data, with a focus on classical methods and structural equation modeling. Throughout the course there will be an emphasis on what kinds of research questions and different types of method can be used to explore repeated measures data.
Learning Outcomes The students who succeeded in this course;
  • will be able to define key concepts in analyzing repeated measures data.
  • Will be able to distinguish different statistical approaches used in analyzing repeated measures data.
  • Will be able to correctly specify research hypotheses in repeated measures design.
  • Will be able to correctly apply statistical techniques to repeated measures data by using different statistical package programs (SPSS and Mplus) used in analyzing repeated measures data.
  • Will be able to correctly interpret results of analyses of psychological data.
  • Will be able to clearly convey orally and in writing the details of statistical analyses and results.
Course Description In this course, students will be informed about repeated measures designs used in experimental psychology and the methodological advantages and disadvantages of these designs. After the students have theoretical background about mentioned methods, they will also be informed about the statistical analyses used for repeated measures data. The course consists of the techniques used for repeated measures data such as univariate analysis (ANOVA and ANCOVA), multivariate analysis (MANOVA and MANCOVA) and Latent Growth Models based on structural equation modeling. Additionally, it is aimed for students to be able to apply these analyses by using SPSS and Mplus programs.
Related Sustainable Development Goals

 



Course Category

 Core Courses
Major Area Courses
X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Brief description of the course content
2 Repeated Measurements, Advantages and Disadvantages of Repeated Measurements Designs Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer, Chapter 1
3 Comparing two means: dependent t-test Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer, Chapter 2
4 Repeated Measures ANOVA: fixed effects Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer, Chapter 5
5 Repeated Measures ANOVA: random effects Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer, Chapter 5
6 Mixed Effects Model Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer, Chapter 6
7 Mixed Effects Model Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer, Chapter 6
8 Midterm Exam
9 Structural Equation Modeling Approach in repeated measures Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley, Chapter 1
10 Latent Growth Models Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley, Chapter 2
11 Latent Growth Models Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley, Chapter 2
12 Latent Growth Models Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach, Chapter 2
13 Latent Growth Curve Models Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley, Chapter 7
14 Latent Growth Curve Models Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley, Chapter 7
15 Latent Growth Curve Models Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley, Chapter 7
16 Review
Course Notes/Textbooks Davis, C (2002). Statistical Methods for the Analysis of Repeated Measurements. New York: Springer. Bollen, K. A. & Curran, P. J. (2006). Latent curve models: A structural equation approach. Hoboken, NJ: Wiley. Muthe´n, L. K., & Muthe´n, B. O. (1998-2015). Mplus users’ guide. Los Angeles, CA: Muthe´n & Muthe´n.\n
Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
4
40
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
30
Final Exam
1
30
Total

Weighting of Semester Activities on the Final Grade
5
60
Weighting of End-of-Semester Activities on the Final Grade
1
40
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
16
5
80
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
4
10
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
1
25
Final Exams
1
32
    Total
225

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
 Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to develop and deepen the current and advanced knowledge in the experimental science of psychology with original thought and/or research and come up with innovative definitions based on Master's degree qualifications.

 X
2

To be able to conceive the interdisciplinary interaction which the experimental psychology is related with, come up with original solutions by using knowledge requiring proficiency on analysis, synthesis and assessment of new and complex ideas.

 X
3

To be able to evaluate and use new methodological knowledge in a systematic way and gain higher level of skills on research methodology of the mind, behavior, and the brain.

 X
4

To be able to develop an innovative knowledge, method, design and/or practice or adapt an already known knowledge, method, design and/or practice to another field; research, conceive, design, adapt and implement an original subject.

 X
5

To be able to make critical analysis, synthesis and evaluation of new and complex ideas in the field of experimental psychology.

 X
6

To be able to develop new ideas and methods in the field of experimental psychology by using high level mental processes such as creative and critical thinking, problem solving and decision making.

 X
7

To be able to broaden the borders of the knowledge in the field by producing or interpreting an original work or publishing at least one scientific paper in the field in national and/or international refereed journals.

 X
8

To be able to organize and participate in scientific activities such as workshops, conferences, and panels to elaborate possible solutions to the problems which may be specific to experimental psychology or interdisiplinary.

 X
9

To be able to contribute to the transition of the community to an information society and its sustainability process by introducing scientific, technological, social or cultural improvements by following pioneer and innovative methods and theories of the mind, behavior and the brain trilogy.

 X
10

To be able to develope effective and functional means of communication to analyze mental relations and processes in the context of experimental psychology.

 X
11

To be able to contribute to the solution finding process regarding social, scientific, cultural and ethical problems in the field and support the development of these values.

 X
12

To be able to write an original dissertation in accordance with the criteria related to the field of Experimental Psychology.

 X
13

To be able to communicate and discuss orally, in written and visually with peers by using English language.

 X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest