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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS PSI 6148 LATENT CLASS ANALYSIS ELECTIVE 3 0 0 5

Offered By

PSYCHOLOGY

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR DUYGU GÜNGÖR CULHA

Offered to

PSYCHOLOGY

Course Objective

In this course, latent classroom analysis applications will be introduced. The aim of the course is for students to learn to use categorical latent variable models.

Learning Outcomes of the Course Unit

1   1. Classification of latent variable models 2   2. Being able to design research in accordance with the latent class model 3   3. Ability to test latent class models with different package programs 4   4. Ability to organize data for latent class analysis 5   5. Ability to define longitudinal latent class models 6   6. To be able to discuss the difference between latent class models and other implicit variables.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 1 Introduction of the course and its requirements 2 2 Fundamentals of latent class analysis 3 3 Parameters in the latent class model 4 4 Interpretation of item response probabilities 5 5 Calculation of latent class probabilities 6 6 Examining the relationship between latent and indicator variables 7 7 Midterm Exams 8 8 Model Selection 9 9 Applications of advanced latent class analysis 10 10 Latent class analysis for repeated measures 11 11 Fundamentals of the Latent Markov model 12 12 Latent Markov model applications 13 13 Simulation applications 14 14 Lesson review

Recomended or Required Reading

Collins, L. Lanza, S. (2009). Latent class and latent transition analysis, Wiley Publication, New Jersey. Hagenaars,J.A., McCutcheon, A.L. (2002). Applied latent class analysis, Cambridge University Press, London.

Planned Learning Activities and Teaching Methods

Lesson Presentation Q&A Homework Discussion

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 STT TERM WORK (SEMESTER) 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + STT * 0.20 + FIN* 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.20 + RST* 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

LO 1-6: It will be evaluated with midterm exam, homework/presentation and final exam.

Language of Instruction

English

Course Policies and Rules

Attendance at 70% of the classes is obligatory.

Contact Details for the Lecturer(s)

duygu.gungor@deu.edu.tr

Office Hours

Tuesday 14:00-15:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 14 4 56 Preparation for midterm exam 1 6 6 Preparation for final exam 1 5 5 Preparation for quiz etc. 1 5 5 Preparing assignments 1 4 4 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 120

Contribution of Learning Outcomes to Programme Outcomes

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