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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS PSI 5082 LATENT VARIABLE MODELS ELECTIVE 3 0 0 7

Offered By

PSYCHOLOGY

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR DUYGU GÜNGÖR CULHA

Offered to

PSYCHOLOGY

Course Objective

The aim of this course is to introduce latent variable models.

Learning Outcomes of the Course Unit

1   Being able to define latent variable models. 2   Being able to explain latent variable models. 3   Being able to choose the best method to perform multivariate analyses of a given dataset. 4   Being able to interpret the obtained results. 5   Being able to give examples recent research on the latent variable models 6   Being able to pursue and contribute to current research in the subject of the latent variable models.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to latent variable models 2 Factor analysis 3 Factor analysis 4 latent profile analysis 5 latent profile analysis 6 latent profile analysis 7 Midterm Examination 8 Item Response Theory 9 Item Response Theory 10 Item Response Theory 11 latent class analysis 12 latent class analysis 13 latent class analysis 14 Latent Markov model

Recomended or Required Reading

Bartholomew, D. J., Knott, M., & Moustaki, I. (2011). Latent Variable Models and Factor Analysis: A Unified Approach: Wiley. Langeheine, R., & Rost, J. (2013). Latent Trait and Latent Class Models: Springer US.

Planned Learning Activities and Teaching Methods

Lecture Answer-Question Presentations 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 * 0.30 + FIN* 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + STT * 0.30 + RST* 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

Midterm exa, assignments and final exam.

Assessment Criteria

1. LO 1-3: They will be evaluated by questions in the midterm examination. 2. LO 4-6: They will be evaluated by questions in the final examination.

Language of Instruction

English

Course Policies and Rules

1. Attendance must be at least 70% for the lectures.

Contact Details for the Lecturer(s)

duygu.gungor@deu.edu.tr

Office Hours

Wed: 15.00-16.00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 5 65 Preparation for midterm exam 1 10 10 Preparation for final exam 1 14 14 Preparing presentations 13 4 52 Final 1 3 3 Midterm 1 3 3 TOTAL WORKLOAD (hours) 186

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 4 5 4 LO.2 5 4 4 5 5 LO.3 5 5 4 LO.4 4 5 5 LO.5 4 4 5 4 LO.6 4 4 5 5