Structural equation modelling in psychology 1600-SZD-SPEC-MBP-PS
The aim of the course is to familiarize the participants with methodology of longitudinal studies within structural equation (SEM) framework and within other frameworks (such as e.g., GEE analysis). More specifically, the following topics will be discussed during the course, starting with relatively simple ones and progressing towards more advanced ones: I. Cross-sectional studies vs. longitudinal studies II. Types of longitudinal studies III. The measurement model. The longitudinal CFA model. IV. Longitudinal panel model V. Multigroup longitudinal SEM VI. Longitudinal growth model VII. Moderation and mediation in longitudinal framework VIII. Panel data analysis in R (if enough time) IX. Additional approaches to longitudinal data (GLM, ARIMA, GEE, LMM, GLMM). Additional “small topics” such as e.g., attrition analysis, sensitivity analysis. The course constitutes continuation of “Structural equation modeling”.
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Term 2024Z:
The aim of the course is to familiarize the participants with methodology of longitudinal studies within structural equation (SEM) framework and within other frameworks (such as e.g., GEE analysis). More specifically, the following topics will be discussed during the course, starting with relatively simple ones and progressing towards more advanced ones: I. Cross-sectional studies vs. longitudinal studies II. Types of longitudinal studies III. The measurement model. The longitudinal CFA model. IV. Longitudinal panel model V. Multigroup longitudinal SEM VI. Longitudinal growth model VII. Moderation and mediation in longitudinal framework VIII. Panel data analysis in R (if enough time) IX. Additional approaches to longitudinal data (GLM, ARIMA, GEE, LMM, GLMM). Additional “small topics” such as e.g., attrition analysis, sensitivity analysis. The course constitutes continuation of “Structural equation modeling”. |
Course coordinators
Type of course
Learning outcomes
Knowledge | The graduate knows and understands:
WG_01 - to the extent necessary for existing paradigms to be revised - a worldwide body of work, covering theoretical foundations as well as general and selected specific issues - relevant to a particular discipline
within the social sciences
WG_02 - the main development trends in the disciplines of the social sciences in which the education is provided
WG_03 - scientific research methodology in the field of the social sciences
WK_01 - fundamental dilemmas of modern civilisation from the perspective of the social sciences
Skills | The graduate is able to:
UK_05 - speaking a foreign language at B2 level of the Common European Framework of Reference for Languages using the professional terminology specific to the discipline within the social sciences, to the extent enabling participation in an international scientific and professional environment
Social competences | The graduate is ready to
KO_01 - fulfilling the social obligations of researchers and creators
KO_02 - fulfilling social obligations and taking actions in the public interest, in particular in initiating actions in the public interest
KO_03 - think and acting in an entrepreneurial manner
And others: As a result of attending the proposed course, PhD students will be able to :•understand basic ideas behind methodology of longitudinal studies •distinguish between various types of longitudinal models and different ways of analyzing longitudinal models •being able to apply an adequate technique to analyze longitudinal data within given research problem •analyze longitudinal data within the SEM framework using statistical software (SPSS, Amos, R) •evaluate and describe the results in the impacted alike publication form
Assessment criteria
Description of requirements related to participation in classes, including the permitted number of explained absences: • requirements at the entrance: knowledge of English, basic idea of statistical software (SPSS, Amos, and R) highly recommended •Permitted number of explained absences: 1 meeting out of 5
Principles for passing the classes and the subject (including resit session): active participation in the course; preparation of one larger project at the end of the course
Methods for the verification of learning outcomes: preparation of a one larger project which will require data analysis using the techniques taught during the course with adequate description of the results in the form of a results chapter (such the ones which are usually prepared for scientific data dissemination in journals with impact factor)
Evaluation criteria: adequacy of choice of structural equation model to the given longitudinal data, correctness of statistical analysis, correctness of results interpretation, clarity and quality of results description
Bibliography
(1) Little, T. D. (2013). Longitudinal structural equation modeling. Guilford press.o
(2) Selig, J. P., & Little, T. D. (2012). Autoregressive and cross-lagged panel analysis for longitudinal data.
(3) Garson, G. D. (2013). Generalized Linear Models & Generalized Estimating Equations. Statistical Associates Publishers: Asheboro.
(4) Garson, G. D. (2013). Longitudinal Analysis. Statistical Associates Publishers: Asheboro. Dodatkowa literatura może zostać zaproponowana tuż przed rozpoczęciem kursu
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Term 2024Z:
(1) Little, T. D. (2013). Longitudinal structural equation modeling. Guilford press.o |
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: