Wolfgang Viechtbauer

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Teaching

    • Contents: Graduate level course on methods for meta-analysis. Topics covered include: steps of a systematic review, extracting/calculating effect sizes and outcome measures for meta-analyses, equal/fixed/random/mixed-effects models, moderator analyses (meta-regression and subgrouping), model diagnostics (identifying outliers and influential studies) and sensitivity analyses, publication bias, multilevel/multivariate/network meta-analysis models (for handling dependent/correlated outcomes), missing data, and meta-analytic techniques for individual participant data.
    • Roles: Course Coordinator, Lecturer, Tutorial Instructor.
    • Taught: Freie Universität Berlin 2014, Tilburg University 2012-2018, University of Bern 2013/2017, Experimental Psychopathology (EPP) Post-Graduate School 2013, Cologne International Summer University 2013, Graduate School for Production Ecology & Resource Conservation (PE&RC) 2012, IMPRS Uncertainty Summer School 2011, Maastricht University 2009, University of Mannheim 2008, European Association of Personality Psychology (EAPP) Summer School 2009, Interuniversity Graduate School of Psychometrics and Sociometrics (IOPS) 2006/2008/2011/2014/2016/2018, University of Basel 2017, University of Illinois at Urbana-Champaign 2017, Heidelberg University 2018, University of Zurich 2022, Online 2020-2022, University of Murcia 2023.
    • Contents: Graduate level course on advanced methods for meta-analysis. Topics covered include: multilevel and multivariate models for meta-analysis, methods for dealing with dependent/correlated outcomes, network meta-analysis (multiple/mixed treatment comparisons), models with crossed random effects, and phylogenetic meta-analysis.
    • Roles: Course Coordinator, Lecturer, Tutorial Instructor.
    • Taught: Vanderbilt University 2015, Flanders Training Network for Methodology and Statistics (FLAMES) Summer School 2019, Conference of the Section Methods and Evaluation of the German Psychological Society 2019.
    • Contents: Graduate level course on methods for analyzing intensive longitudinal data as collected in studies using experience sampling method. Topics covered include: introduction to ESM and related methods, data checking/preparation/cleaning, mixed-effects models for analyzing multilevel data (random intercepts and slopes models), models allowing for correlation in the residuals (serial/autocorrelation), models with more than two levels, checking model assumptions, model selection/comparison/testing, models for other types of outcomes (e.g., dichotomous, multinomial, ordinal), psychometrics (reliability, validity, factor analysis with multilevel data), power analysis, and various advanced topics.
    • Roles: Course Coordinator, Lecturer, Tutorial Instructor.
    • Taught: Maastricht University 2014/2015/2018/2019, University of Leuven 2017, University of Zurich 2018, Online 2021/2023.
    • Contents: Graduate level course on the statistical programming language R. Topics covered include: history of R, basic data structures, data import/export, data inspection/manipulation, methods for graphing data, statistical methods for continuous and categorical data, strategies for finding and working with add-on packages, programming structures, writing documents with R Markdown.
    • Roles: Course Coordinator, Lecturer, Tutorial Instructor.
    • Taught: Maastricht University 2012/2014-2016/2019-2023, Online 2020 (3x).
  • Stat Lunch
    • Contents: A semi-regular series of lectures (in the spirit of a brown bag seminar) provided to members of the Department of Psychiatry and Neuropsychology and the School for Mental Health and Neuroscience. Topics include a wide variety of statistical and methodological issues.
    • Role: Lecturer.
    • Taught: Maastricht University 2013-2015.
  • ESM Course
    • Contents: Two/three-day workshop providing an introduction to the methodological and practical aspects of conducting research using the experience sampling method (ESM) in psychopathology research and other areas. Topics covered include: background on the experience sampling method, techniques used in collecting intensive longitudinal data, questionnaires development and structure, statistical methods used for analyzing ESM data, and practical aspects of implementing ESM studies.
    • Role: Lecturer.
    • Maastricht University 2014-2023, University of Leuven 2019/2022-2023.
  • Psychiatric Epidemiology
    • Contents: Graduate level seminar providing an introduction to the methods and analytical strategies of epidemiology as applied to mental health outcomes. The principles and practice of various study types (e.g., cohort, case-control, RCT) are described, with emphasis on interpreting associations and possible causality thereof. Consideration is given to such issues as confounding, bias, and effect modification. Further topics covered include the use and interpretation of diagnostic studies, the basic principles of analyzing dichotomous, count, and time-to-event outcomes (i.e., logistic regression, Poisson regression, survival analysis), and the use of systematic reviews and meta-analysis for building cumulative knowledge.
    • Roles: Course Coordinator, Lecturer.
    • Taught: Maastricht University 2013-2023.
  • Psychometrics Practicum
    • Contents: Graduate level seminar that provides a thorough overview of the basic principles of psychological measurement (i.e., psychometrics). Topics that are covered include: classical test theory, reliability analysis (e.g., test-retest, parallel forms, split-half, Cronbach's alpha), validity (e.g., content, criterion, construct), principal component analysis, factor analysis (exploratory and confirmatory), and item response theory.
    • Role: Course Coordinator, Lecturer.
    • Taught: Maastricht University 2012-2023.
  • Research Methods I and II & Research Proposal Writing
    • Contents: Three course sequence providing an introduction to research methods in the social and health sciences. Topics covered include: the scientific method and conceptual foundations of research, correlational, experimental, and quasi-experimental research, experimental design, measurement, sampling, survey research, questionnaire construction, data preparation and analysis, research ethics, and research proposal writing.
    • Roles: Course Coordinator, Lecturer, Tutorial Instructor.
    • Taught: Maastricht University 2005-2010.
  • Factor Analysis and Multilevel Data Analysis
    • Contents: Graduate level course for students in various Master level programs. Topics covered include: principal component analysis, exploratory and confirmatory factor analysis, and hierarchical linear modeling for multilevel and repeated measures designs.
    • Roles: Planning Group Member, Lecturer, Tutorial Instructor.
    • Taught: Maastricht University 2007-2010.
  • Statistical Methods 3.2B
    • Contents: Methods and techniques for evaluation research, analysis of variance and multiple regression with dummy-coded variables, analysis of covariance, analysis of repeated measurements with ANOVA and multivariate methods, sample size calculations, systematic reviews, and meta-analysis.
    • Role: Tutorial Instructor.
    • Taught: Maastricht University 2007-2008.
  • Statistical Methods 2.1B
    • Contents: Experimental design in epidemiological research, methods for qualitative research, classical test theory and test development, multiple linear regression, and logistic regression.
    • Role: Tutorial Instructor.
    • Taught: Maastricht University 2006-2010.
  • Statistical Methods 1.3
    • Contents: Introduction to research methods in the health sciences; research design, qualitative research, descriptive statistics, correlation, and simple linear regression.
    • Role: Tutorial Instructor.
    • Taught: Maastricht University 2008-2009.
  • Statistical Methods II
    • Contents: Graduate level course covering complex experimental designs with emphasis on the general linear model, including Latin Squares, factorial, nested and split-plot designs, analysis of covariance, repeated-measures designs, random- and mixed-effects models, nonparametric methods, and categorical data analysis.
    • Role: Teaching Assistant.
    • Taught: University of Illinois 2000-2003.
  • Statistical Methods I
    • Contents: Graduate level course covering various techniques in applied statistics used in psychological research, including linear regression, partial and multiple correlation, thorough review of statistical estimation and significance testing, experimental design, ANOVA, and statistical computing.
    • Role: Teaching Assistant.
    • Taught: University of Illinois 2000-2003.
  • Introduction to Statistics
    • Contents: Development of skill and understanding of statistical methods in psychological research. Topics covered include: descriptive statistics, basic probability theory and distributions, point and interval estimation, and hypothesis testing.
    • Role: Teaching Assistant.
    • Taught: University of Illinois 1998-1999.
teaching.txt · Last modified: 2024/02/01 09:25 by Wolfgang Viechtbauer