Longitudinal Data Analysis - JSM468
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This course introduces the quantitative analysis of longitudinal survey data for master's and doctoral students in sociology (and related social science disciplines). The course covers preparing Czech panel survey data (e.g. Czech Household Panel Survey, Czech Attitude Barometer) for analysis. After introductory methods like repeated-measures ANOVA, students will explore advanced techniques, including multilevel modelling for longitudinal data, structural equation modelling, latent growth curve analysis, and survival analysis. Emphasis is placed on both theoretical understanding and practical application through hands-on exercises. The course will utilize the IBM SPSS Statistics software. Enrolled students will receive a license for this software from the Faculty of Social Sciences. Last update: Petrúšek Ivan, Mgr., Ph.D. (16.01.2025)
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Hoffman, L. 2014. Longitudinal Analysis: Modeling Within-Person Fluctuation and Change (Multivariate Applications Series). Routledge. Longhi, S., A. Nandi. 2014. A Practical Guide to Using Panel Data. Sage. Singer, J. D., J. B. Willett. 2003. Applied longitudinal data analysis: Modeling change and event occurrence. Oxford University Press. Field, A. 2009. Discovering statistics using SPSS. Sage. Last update: Petrúšek Ivan, Mgr., Ph.D. (16.01.2025)
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Teaching units: Blocks (every other week), each consisting of a lecture (80 minutes) and a seminar (80 minutes). Six blocks (days of teaching) will take place during the semester. While no extensive knowledge of statistical methods is required to attend this course, registered students should be familiar with the basics of statistical hypotheses testing and OLS linear regression. Students not familiar with the basics of the IBM SPSS Statistics software will be provided with a video by Petr Soukup (i.e. one of the course tutors), which introduces the IBM SPSS Statistics environment and basic data management procedures. Last update: Petrúšek Ivan, Mgr., Ph.D. (27.01.2025)
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Grading is based on four homework assignments and a draft (article). Every part is evaluated separately, and a student may earn between 0% and 100% for each part. Weights for final evaluation are as follows: each homework assignment is 10%, and the draft is 60%. Homework assignments must be submitted within 14 days of being assigned (i.e. students have two weeks to complete each assignment). Homework assignments are submitted electronically to the email address lda.iss@fsv.cuni.cz The draft (article) is due on Monday, 17th June 2025, at 11 am (drafts are submitted electronically to the email address lda.iss@fsv.cuni.cz). Draft (article) should follow a common academic structure: problem formulation (derived from theory), hypotheses formulation and statistical analysis for hypotheses evaluation (employing at least two techniques from the syllabus). The draft must be between 4000 and 4500 words (excluding tables, figures and references). The draft article should adhere to the APA citation standard (https://en.wikipedia.org/wiki/APA_style). The draft must include an abstract of around 150-200 words and an IBM SPSS Statistics syntax that enables full replication of results reported in the draft. Further details on the draft articles will be communicated in class and via email to registered students. Grading (based on the total weighted percentage earned):
NOTE: Total weighted percentages earned will be rounded to the whole number (e.g., the overall result of 50.5% is rounded to 51%, corresponding to the grade E). Last update: Petrúšek Ivan, Mgr., Ph.D. (24.02.2025)
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The six teaching blocks of the course will be organized as follows: 1. Introduction to Czech Household Panel Survey data. Data preparation for longitudinal data analysis. 2. Paired t-test, repeated-measures ANOVA. 3. Introduction to longitudinal multilevel models. 4. Mixed multilevel models for longitudinal data. 5. SEM and latent growth-curve models. 6. Survival analysis. Last update: Petrúšek Ivan, Mgr., Ph.D. (16.01.2025)
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