• HOME
• ABOUT US
  • Name Address
  • General Description
  • Governance
  • Academic Calendar
  • Degree Programmes
  • List of Programmes in English
  • General Admission and Registration Procedures
  • Credit Mobility and Recognition of Prior Learning
  • ECTS Credit Allocation
  • Academic Guidance
  • Contacts
• Degree Programmes
  • Third Cycle Programmes (Doctorate Degree)
  • Second Cycle Programmes (Master's Degree)
  • First Cycle Programmes (Bachelor's Degree)
  • Short Cycle Programmes (Associate's Degree)
• GENERAL INFORMATION FOR STUDENTS
  • Cost of Living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Disabled Students
  • Insurance
  • Financial Supports
  • Student Affairs Office
  • Practical Information for International Students
  • Language Courses
  • Work Placement Possibilities
  • Sports, Social and Cultural Facilities
  • Student Associations and Clubs
  • About İzmir - Turkey
• INTERNATIONAL RELATIONS
  • International Relations Office
  • Registration Procedures
  • Agreements
  • Coordinators
  • Documents
  • List of Programmes in English
  • ECTS / DS Labels

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS PSI 6122 STRUCTURAL REGRESSION MODELING ELECTIVE 3 0 0 5

Offered By

PSYCHOLOGY

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

ASSOCIATE PROFESSOR DUYGU GÜNGÖR CULHA

Offered to

PSYCHOLOGY

Course Objective

The goal of this course is to teach the students; construction, analysis, modifying, and testing the adequacy of variety of structural equation models and report the results of their analyses.

Learning Outcomes of the Course Unit

1   Will be familiarized with the language, logic, and implementation of structural equation modeling 2   Compare and contrast structural equation modeling with more commonly used statistical procedures such as analysis of variance, multiple regression analysis, and factor analysis; 3   Learn the criteria associated with decisions that must be made at each phase of a structural equation modeling analysis 4   Consider the philosophical and statistical criticisms of structural equation modeling as an approach to research design and data analysis 5   Be able to apply appropriate statistical model for psychological data analysis 6   Be able to interpret the results of structural equation model analysis correctly and report the results

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 What is Structural Equation Modeling (SEM) 2 Basic concepts and notations 3 Basic Concepts: the data, the estimates (model parameters) 4 Types of models and their specification in a diagram 5 Path Analysis 6 Measurement models: Firstorder confirmatory factor analysis 7 Measurement models : Higherorder confirmatory factor analysis 8 Multigroup applications of CFA 9 Midterm Exam 10 Structural Regression Models 11 Structural Regression Models 12 Multigroup applications of structural models 13 Examples from the literature 14 Review

Recomended or Required Reading

Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed). New York: Guilford Press.

Planned Learning Activities and Teaching Methods

Lecture Presentation Questions-Answers Homework Discussions

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 PRJ PROJECT 3 PRS PRESENTATION 4 FIN FINAL EXAM 5 FCG FINAL COURSE GRADE MTE* 0.20 + PRJ* 0.20 + PRS* 0.20 + FIN* 0.40 6 RST RESIT 7 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + PRJ * 0.20 + PRS * 0.20 + RST* 0.40

Further Notes About Assessment Methods

1. Midterm 2. Term Project 3. Presentation 4. Final

Assessment Criteria

LO 1-2: Assessed with Midterm exam LO 3-5: Assessed with homework/report, presentation and final exam

Language of Instruction

Turkish

Course Policies and Rules

Seventy percent attendance is obligatory

Contact Details for the Lecturer(s)

duygu.gungor@deu.edu.tr

Office Hours

Tuesday 11:00-12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Tutorials 6 1 6 Preparations before/after weekly lectures 14 2 28 Preparation for midterm exam 1 10 10 Preparation for final exam 1 10 10 Preparation for quiz etc. 2 10 20 Preparing assignments 1 10 10 Midterm 1 3 3 Final 1 3 3 TOTAL WORKLOAD (hours) 132

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 LO.1 4 4 4 5 4 LO.2 4 4 4 5 4 LO.3 4 5 4 5 5 LO.4 4 5 4 5 4 LO.5 5 5 4 5 5 LO.6 5 5 4 5 4