FSS:PSYn5440 Introduction to Factor Analysi - Informace o předmětu
PSYn5440 Introduction to Factor Analysis
Fakulta sociálních studiípodzim 2024
- Rozsah
- 0/2/0. 4 kr. Ukončení: zk.
Vyučováno kontaktně - Vyučující
- doc. Mgr. Stanislav Ježek, Ph.D. (přednášející)
Mgr. et Mgr. Petr Palíšek (přednášející)
Bc. Anna Literová (pomocník) - Garance
- Mgr. et Mgr. Petr Palíšek
Katedra psychologie – Fakulta sociálních studií
Dodavatelské pracoviště: Katedra psychologie – Fakulta sociálních studií - Rozvrh
- Po 18:00–19:40 P24b
- Předpoklady
- ! PSY544 Introduction to Factor Analysis
Students are strongly recommended to have taken at least an elementary course in statistical data analysis. Solid understanding of multiple linear regression is beneficial, as is at least basic knowledge of R. Students with zero or little previous exposure will be given resources and time to catch up and will be expected to do so. - Omezení zápisu do předmětu
- Předmět je nabízen i studentům mimo mateřské obory.
Předmět si smí zapsat nejvýše 25 stud.
Momentální stav registrace a zápisu: zapsáno: 9/25, pouze zareg.: 0/25, pouze zareg. s předností (mateřské obory): 0/25 - Mateřské obory/plány
- Psychologie (program FSS, N-PS)
- Psychologie (program FSS, N-PSY)
- Cíle předmětu
- After successfully taking the course, the student will:
Have a deeper understanding of factor analysis than is usual in broader, general courses of statistical data analysis offered in most psychology programs;
Be knowledgeable about the mathematical formulation and the reasoning behind the Common Factor Model;
Know the methods for fitting the model on data and evaluating model fit, common estimation methods and problems related to the model and its use;
Be able to apply unrestricted (exploratory) and restricted (confirmatory) factor models using different software;
Understand the principles of analytical rotation; - Výstupy z učení
- After successfully taking the course, the student will:
- know the mathematical formulation and the reasoning behind the Common Factor Model;
- know the methods for fitting the model on data and evaluating model fit;
- know common estimation methods;
- understand the principles of analytical rotation;
- be able to recognize and troubleshoot problems related to the model and its use;
- be able to apply unrestricted (exploratory) and restricted (confirmatory) factor models using different software. - Osnova
- Introduction: What is factor analysis? Objectives, goals and principles.
- Exploratory vs. Confirmatory factor analysis.
- Matrix algebra basics: Scalars, vectors and matrices
- Basic matrix and vector operations and functions.
- The fundamental equations of factor analysis.
- Mean, covariance and correlation structures.
- Methods of fitting the model on data.
- Model identification and rotational indeterminacy.
- Fitting the model on population and sample correlation matrices.
- The communality problem. Iterative and non-iterative estimation – Principal Factors Method, Ordinary Least Squares, Maximum Likelihood.
- Heywood cases.
- Evaluating model fit.
- Fitting the unrestricted model with software.
- Common rules of thumb and guidelines for choosing the number of factors. Alternative methods - parallel analysis, minimum average partial.
- Goodness-of-fit tests. Common fit indices.
- Rotation. The concept of rotation and simple structure.
- Orthogonal rotations, oblique rotations, target rotation.
- Restricted (confirmatory) factor analysis.
- Constraints, restrictions and identification conditions.
- Parameter matrices. Free and fixed parameters. Path diagrams.
- Common estimation methods.
- Fitting the restricted model with software.
- Goodness of fit in CFA. Methods and processes for evaluating model fit. Common fit indices. Tests of good fit.
- Comparing different models.
- Special topics Bi-factor models. Group models. Differences between Principal Components Analysis and Factor Analysis. Classical Test Theory Applications.
- Literatura
- MULAIK, Stanley A. Foundations of factor analysis. Second edition. Boca Raton: CRC Press, Taylor & Francis Group, 2010, xxiii, 524. ISBN 9781420099614. info
- Výukové metody
- Two 50-minute lectures per week, individual homework assignments
- Metody hodnocení
- Three homework assignments, final take-home exam, individual examination and discussion over the submitted exam
- Vyučovací jazyk
- Angličtina
- Navazující předměty
- Další komentáře
- Studijní materiály
Předmět je vyučován každoročně.
- Statistika zápisu (nejnovější)
- Permalink: https://is.muni.cz/predmet/fss/podzim2024/PSYn5440