Subjects

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Statistical Methods in Psychometrics - NMST570

Title:	Statistické metody v psychometrii
Guaranteed by:	Department of Probability and Mathematical Statistics (32-KPMS)
Faculty:	Faculty of Mathematics and Physics
Actual:	from 2023
Semester:	winter
E-Credits:	3
Hours per week, examination:	winter s.:1/1, C+Ex [HT]
Capacity:	unlimited
Min. number of students:	unlimited
4EU+:	no
Virtual mobility / capacity:	no
State of the course:	taught
Language:	Czech, English
Teaching methods:	full-time
Teaching methods:	full-time
Additional information:	https://www.cs.cas.cz/martinkova/NMST570.html

Guarantor:	doc. RNDr. Patrícia Martinková, Ph.D.
Class:	Pravděp. a statistika, ekonometrie a fin. mat. M Mgr. PMSE M Mgr. PMSE > Volitelné
Classification:	Mathematics > Probability and Statistics
Comes under:	PVP Pedagogika - PedF

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Annotation -

Last update: RNDr. Jitka Zichová, Dr. (09.05.2018)

Psychometrics uses statistical models for analysis of educational and psychological tests. This course covers main topics in psychometrics, such as traditional item analysis, reliability and validity of measurement, use of logistic and nonlinear regression models, item response theory models, differential item functioning, computerized adaptive testing, etc. Methods are demonstrated using data from Czech matura examination, admission tests and other assessments. Exercises are prepared in freely available statistical software R, other psychometric software is also introduced.

Aim of the course -

Last update: doc. RNDr. Patrícia Martinková, Ph.D. (01.10.2023)

The goal of the course is to present the main topics of psychometrics and selected methods for the analysis of educational end psychological tests.

Course completion requirements -

Last update: doc. RNDr. Patrícia Martinková, Ph.D. (01.10.2023)

Active presence, satisfactory solutions to assignments, final project.

Literature -

Last update: doc. RNDr. Patrícia Martinková, Ph.D. (01.10.2023)

Martinková, P., & Hladká, A. (2023). Computational Aspects of Psychometric Methods: With R (1st ed.). Chapman and Hall/CRC. https://doi.org/10.1201/9781003054313

Teaching methods -

Last update: RNDr. Jitka Zichová, Dr. (09.05.2018)

Lecture + exercises.

Requirements to the exam -

Last update: doc. RNDr. Patrícia Martinková, Ph.D. (05.11.2019)

Final project (50%) and homework assigned during the course (50%).

Syllabus -

Last update: doc. RNDr. Patrícia Martinková, Ph.D. (07.05.2018)

Traditional item analysis

Reliability and validity

Regression models for item description

Item response theory (IRT) models

Differential item functioning (DIF)

Computerized adaptive testing (CAT)

Entry requirements -

Last update: RNDr. Jitka Zichová, Dr. (30.05.2019)

Basic knowledge of statistical methods.