Advanced Longitudinal Analyses using Structural Equation Modeling, 7,5 hp

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1 Syllabus Advanced Longitudinal Analyses using Structural Equation Modeling, 7,5 hp Avancerade longitudinella analyser med strukturell ekvationsmodellering (SEM), 7,5 Higher Education Credits Course Code: 35SEM28 Valid from: Spring semester 2013 Level of Study: Third cycle Established: Subject Area: Psychology Approved by: Head of School Higher Education Credits: 7,5 Aims and objectives General aims for third level education Third level education shall essentially build on the knowledge that students acquire in first level and second level education or corresponding knowledge. In addition to what applies to first level and second level education, third level education shall develop the knowledge and skills needed to be able to conduct research independently (Higher Education Act, Chapter 1, Section 9 a). The specific national expected learning outcomes in accordance with the Higher Education Ordinance for the degree of doctor and the licentiate degree can be found in appendix 1 to the general syllabus for the subject. Course objectives This course is a follow-up of the Structural Equation Modelling: Theory and Application. Successful completion of this first introductory course or a similar introductory course is a prerequisite for attending the current course. The main aim of this course is to review the theoretical background and application of advanced longitudinal data analysis with structural equation modelling (SEM) techniques. The emphasis will be on front-edge and novel longitudinal statistical techniques. The course will be composed of two integral parts: Theory and Application (using Mplus software). First, the course will provide a an overview of theoretical considerations regarding advanced longitudinal modelling. The course will deal with the issues of model building, model comparison, model specification and identification for several modelling techniques (e.g., Cross-Lagged Modelling, Longitudinal Growth Modelling, longitudinal mediation and moderation).the conceptual overviews of each analytical technique will be illustrated by relevant examples. In the application part, the students will learn how to use Mplus software to specify and test longitudinal models discussed theoretically. Students are required to complete practice assignments to

2 enhance their understanding of the statistical techniques, and develop skills of independently applying analytical procedures. Knowledge and understanding After completing the course, students will: - have an understanding of longitudinal model building, (re-)specification, identification, and testing - have in-depth knowledge about advanced SEM techniques (e.g., Cross-Lagged Modelling, Longitudinal Growth Modelling) - understand the assumptions underlying longitudinal SEM techniques - understand strengths and weaknesses of various longitudinal SEM techniques - understand statistical inference based on longitudinal SEM models Skill and ability After completing the course, the students will: - be able to identify the appropriate analytical and estimation longitudinal analysis by taking into account the characteristic of data - be able to identify the longitudinal analytical technique taking into account the research question - be able to develop a conceptual model to test using longitudinal SEM approaches - be able to identify the strengths and weaknesses of different longitudinal SEM techniques - be able to test whether basic assumptions of longitudinal SEM models are met - be able to fit longitudinal models with Mplus software After completing the course the student will have advanced ability to - critically reflect on strengths and weaknesses of different types of longitudinal SEM models - identify the appropriate longitudinal modelling technique for a given conceptual model and research question - critically think about the use of longitudinal SEM procedures to test models and research questions - critically think about statistical inferences taking into account the characteristics of longitudinal data, and longitudinal design of the study Main content of the course The course gives the students - Longitudinal data characteristics and assumptions of data to be used in SEM modeling - Longitudinal model building in SEM framework - Longitudinal model testing using Mplus software - Major strengths and weaknesses of the common longitudinal SEM techniques - Use of model fit statistics to evaluate longitudinal SEM models - Proper and responsible use of longitudinal SEM procedures Reading list and other teaching materials Little, Todd D., Bovaird, James A., & Card, Noel A. (2007) Modeling Contextual Effects in Longitudinal Studies. Lawrence Erlbaum Associates. Mahwah, New Jersey. Finkel, Steven E. (1995) Causal Analysis with Panel Data (Quantitative Applications in the Social Sciences). Thousand Oaks, California; Sage, cop. Additional empirical articles and literature will be provided through Blackboard.

3 These need to be read before the course starts. NB! Students are required to get SPSS software and Mplus software installed. Teaching methods This course is a five-day full day course. Each of the days consists of two sessions. The first session of the day will deal with the conceptual and theoretical basis of advanced SEM modeling. The second session of the day will provide students with applied experiences of what they have learned in the first session. The students are expected to complete assignments during class and an exam on the last day. The combined grade of the assignments and the exam will be the final grade for the course. Attendance to all course sessions is mandatory. The students need to bring their own laptop computers (with Windows operating system) with the software SPSS (15.0 or higher) and Mplus (version 5.0 or higher) installed. The students are individually responsible for obtaining this software. The assignments and exams will include conceptual/theoretical questions, model testing using Mplus, reading and interpreting model fit and estimates. In order to pass the course, the student must have completed all assignments and the exam with a demonstration of in-depth understanding of and skills of using SEM techniques to answer research questions. Blackboard will be used to provide additional readings, handouts, and data files for assignments and exam. The course will be given in English. Research students who have been admitted to a course have the right to receive tuition and/or supervision for the duration of the time period specified for the particular course to which they were accepted. After that, the right to receive tuition and/or supervision expires. Examination methods The assignments and exams will include conceptual/theoretical questions, model testing using Mplus, reading and interpreting model fit and estimates. The exam and assignments will be in English. Grades Examinations included in third level education are to be assessed with one of the grades fail or pass (Vice-Chancellor Decision no 181/2003, reg. no. CF ). Unless otherwise prescribed above, the research student is required to successfully complete all examinations and compulsory modules in order to be awarded the course grade pass. Re-examination Research students who have failed an examination are entitled to a retake. Normally, retakes are offered a certain time period after the first examination was offered.

4 A research student who has failed an examination twice for a specific course or course module is entitled to request, with the head of school, the appointment of another examiner to determine the grade. Admission requirements Research students who have been admitted to third level education at a higher education institution in Sweden, or equivalent programme abroad, have basic eligibility for admission to the course. One of the following two admission requirements needs to be met: 1. Students need to have finished the Introductory course Structural Equation Modelling: Theory and Application (course code 35ST021). 2. Students need to have successfully completed another course on Structural Equation Modelling. A proof of successful completion of the course needs to be approved by Dr. Maarten van Zalk. It needs to be sent two weeks prior to the official start of the course to maarten.vanzalk@oru.se Selection No more than 20 students will be accepted for attendance and examination. In the case of more students applying the following selection criteria will apply. First priority will be given to students who have completed secondary level courses in multiple regression models and factor analysis. Second priority will be given to students admitted to research studies at Örebro University, School of Law, Psychology and Social Work. Third priority will be given to research students from other schools at Örebro University. Any remaining course places will be offered to research students from other higher education institutions. Transfer of credits for previous studies and other activities If a student at a higher education institution in Sweden has successfully completed a certain higher education programme, the student is entitled to credit for this when studying at another higher education institution. This does not, however, apply if there is a substantial difference between the educational programmes. The same applies to students who have successfully completed a certain educational programme at a university or other institution of higher education in Denmark, Finland, Iceland or Norway or in an entity that is party to the Council of Europe Convention of 11 April 1997 on the Recognition of Qualifications concerning Higher Education in the European Region (Swedish Treaty Series 2001:46), or at the Nordic School of Public Health. A student is entitled to credit for an educational programme other than one referred to in Section 6 if the knowledge and skills that the student cites are of such a nature and of such a scope that they essentially correspond to the educational programme toward which they are intended to give credit. A student may also receive credit for corresponding knowledge and skills acquired in the course of working activities. The higher education institution is to consider whether previous education or activities can be accepted for credit (Higher Education Ordinance, Chapter 6, Sections 6-8). Other regulations

5 The students need to bring their own laptop computers (with Windows operating system) and need to have the software SPSS (version 15.0 or higher) and Mplus (Version 5.0 or higher) installed before the course starts. These will not be provided by Örebro University. Each student is required to individually obtain this software. Both Mac and Windows computers can be used. The demo version of Mplus cannot be used. Transitional provisions A research student who has commenced but not completed the course in accordance with the course syllabus established on 7 Mars 2013 has the right to be examined under that course syllabus at least one semester after that during which the course was last offered according to the course syllabus.