dr. Daniel Oberski
Gegenereerd op 2018-08-15 01:55:36


My research focuses on the problem of measurement in the social sciences. To draw accurate substantive conclusions, social scientists need to measure human behavior and opinions reliably and validly. Where this ideal is unattainable, the extent of the problem should be known so it can be accounted for in the substantive analysis. My research has contributed to this by:

  1. Estimating measurement error in hundreds of survey questions from the European Social Survey and creating a meta-analysis that predicts the extent of such errors;
  2. Developing models that correct multivariate social science analyses for the effects of measurement error while retaining accurate measures of uncertainty about the results;
  3. Introducing several novel methods to evaluate the fit of latent variable models, the type of model used to attain the two goals above;
  4. Collaborating on substantive social science research and implementing my own and others’ methods in user-friendly software.

I am also interested in the use of administrative data from government registers, and "big" or social sensor data from devices such as smartphones, browsers, and so forth, to meaningfully measures social variables.


Strategische thema's / focusgebieden
Wetenschappelijke expertises
data mining
latent variable modeling
latente klasse analyse
mixture modeling
unsupervised learning
statistical learning
Gegenereerd op 2018-08-15 01:55:37
Curriculum vitae

I am a member of the Utrecht Young Academy and the Young Academy of the Royal Netherlands Academy of Arts and Sciences.



In 2004–5 I was a cofounding board member of the European Survey Research Association (ESRA). I helped organize the ESRA conferences in Barcelona (2005), Prague (2007), and Warsaw (2009).

From 2006–2011 I worked for the European Social Survey (ESS). As a member of the group in charge of the evaluation of question quality in the ESS I worked on multitrait-multimethod (MTMM) models. At first (2006-2008) we were at the methods department of ESADE, Barcelona, after which we became the Research and Expertise Centre for Survey Methodology (RECSM) at the Universitat Pompeu Fabra (UPF) in Barcelona. During this period I often represented UPF in the central coordinating team of the ESS.

In January 2011 I obtained my PhD in as an external candidate at the department of Methodology and Statistics of Tilburg University. My thesis was entitled “Measurement error in comparative surveys” and the promotors were Professors Willem SarisAlbert Satorra, and Jacques Hagenaars.

Continuing at UPF I worked on a new version of the Survey Quality Predictor (SQP 2.0), a program designed to predict the quality of a survey question from its characteristics such as the number of categories, presence of a “don’t know” option, linguistic complexity, etc. Some results from that work can be found here, and the program is online here.

After this I had the pleasure of being a visiting professor at the Joint Program for Survey Methodology (JPSM) at the University of Maryland, teaching experimental design. During this period I also worked on comparability of survey results across groups.

In January 2012 I joined the Methodology department at Tilburg to work on a project funded by the Dutch National Science Foundation on stepwise latent class modeling.

On 17 July 2014 I was awarded a Veni grant from the Dutch national science foundation, NWO, for the period 2015–2018. On 1 January 2015 I joined the Methodology department as a tenure track assistant professor (tenured 2015).

On 1 September 2016 I joined the Methodology & Statistics department at Utrecht university as an associate professor Data Science methodology.

Gegenereerd op 2018-08-15 01:55:37

This is a non-exhaustive list of peer-reviewed journal articles only. For my full list of publications, preprints, and reproduction materials, please see http://daob.nl/publications

Alle publicaties
  2018 - Wetenschappelijke publicaties
Lek, K.M., Oberski, D.L., Davidov, Eldad, Cieciuch, Jan, Seddig, Daniel & Schmidt, Peter (2018). Approximate measurement invariance. In Timothy P. Johnson, Beth-Ellen Pennell, Ineke Stoop & Brita Dorer (Eds.), Advances in Comparative Survey Methodology (pp. 1-18). Hoboken, New Jersey: John Wiley & Sons Inc..
Boeschoten, Laura, Oberski, Daniel L., Waal, Ton A.G. de & Vermunt, Jeroen K. (2018). Updating latent class imputations with external auxiliary variables. Structural Equation Modeling
  2017 - Wetenschappelijke publicaties
Oberski, D.L. (21-08-2017) Organiser Survey research: Statistical analysis and estimation Utrecht (21-08-2017 - 25-08-2017) Survey research: Statistical analysis and estimation: Summerschool
Borghuis, Jeroen, Denissen, Jaap J A, Oberski, Daniel, Sijtsma, Klaas, Meeus, Wim H J, Branje, Susan, Koot, Hans M & Bleidorn, Wiebke (2017). Big Five Personality Stability, Change, and Codevelopment Across Adolescence and Early Adulthood. Journal of Personality and Social Psychology (c) 2017 APA, all rights reserved)..
Mayor, Jordan R, Sanders, Nathan J, Classen, Aimée T, Bardgett, Richard D, Clément, Jean-Christophe, Fajardo, Alex, Lavorel, Sandra, Sundqvist, Maja K, Bahn, Michael, Chisholm, Chelsea, Cieraad, Ellen, Gedalof, Ze'ev, Grigulis, Karl, Kudo, Gaku, Oberski, Daniel L & Wardle, David A (25-01-2017). Elevation alters ecosystem properties across temperate treelines globally. Nature
Boeschoten, Laura, Oberski, Daniel & De Waal, Ton (01-12-2017). Estimating Classification Errors under Edit Restrictions in Composite Survey-Register Data Using Multiple Imputation Latent Class Modelling (MILC). Journal of Official Statistics, 33 (4), (pp. 921-962) (42 p.).
Oberski, D. L., Kirchner, A., Eckman, Stephanie & Kreuter, Frauke (02-10-2017). Evaluating the Quality of Survey and Administrative Data with Generalized Multitrait-Multimethod Models. Journal of the American Statistical Association, 112 (520), (pp. 1477-1489) (13 p.).
Oberski, D.L. (01-01-2017 01-01-2020) Editorial board member Journal of the Royal Statistical Society. Series C: Applied Statistics (Journal)
Nagelkerke, Erwin, Oberski, Daniel L. & Vermunt, Jeroen K. (2017). Power and Type I Error of Local Fit Statistics in Multilevel Latent Class Analysis. Structural Equation Modeling, 24 (2), (pp. 216-229).
van Erp, Sara, Mulder, Joris & Oberski, Daniel L. (27-11-2017). Prior Sensitivity Analysis in Default Bayesian Structural Equation Modeling. Psychological Methods
  2017 - Vakpublicaties
Oberski, D.L. (01-03-2017). Sexy Data Science. STAtOR, 18 (1), (pp. 34-37).
  2017 - Overige resultaten
Oberski, D.L. 01-01-2017 Recipient Young Academy, KNAW KNAW
  2016 - Wetenschappelijke publicaties
Oberski, D. L. (2016). A review of latent variable modeling with R (vol 41, pg 226, 2016). Journal of Educational and Behavioral Statistics, 41 (3), (pp. 355-355).
Oberski, D. L. (2016). Beyond the number of classes - separating substantive from non-substantive dependence in latent class analysis. Advances in Data Analysis and Classification, 10 (2), (pp. 171-182) (12 p.).
Di Mari, Roberto, Oberski, Daniel L. & Vermunt, Jeroen K. (02-09-2016). Bias-Adjusted Three-Step Latent Markov Modeling With Covariates. Structural Equation Modeling, 23 (5), (pp. 649-660) (12 p.).
Nagelkerke, Erwin, Oberski, Daniel L. & Vermunt, Jeroen K. (2016). Goodness-of-fit of multilevel latent class models for categorical data. Sociological Methodology, 46 (1), (pp. 252-282) (31 p.).
Molenaar, Dylan, Oberski, Daniel, Vermunt, Jeroen & De Boeck, Paul (02-09-2016). Hidden Markov Item Response Theory Models for Responses and Response Times. Multivariate Behavioral Research, 51 (5), (pp. 606-626) (21 p.).
Lamont, Andrea, Lyons, Michael D, Jaki, Thomas, Stuart, Elizabeth, Feaster, Daniel J, Tharmaratnam, Kukatharmini, Oberski, Daniel, Ishwaran, Hemant, Wilson, Dawn K & Van Horn, M Lee (2016). Identification of predicted individual treatment effects in randomized clinical trials. Statistical Methods in Medical Research © The Author(s) 2016..
Gallego, Aina, Buscha, Franz, Sturgis, Patrick & Oberski, Daniel (2016). Places and Preferences: A Longitudinal Analysis of Self-Selection and Contextual Effects. British Journal of Political Science, 46 (3), (pp. 529-550).
Van Smeden, Maarten, Oberski, Daniel L., Reitsma, Johannes B., Vermunt, Jeroen K., Moons, Karel G M & De Groot, Joris A H (01-06-2016). Problems in detecting misfit of latent class models in diagnostic research without a gold standard were shown. Journal of Chronic Diseases, 74, (pp. 158-166) (9 p.).
Bakk, Zsuzsa, Oberski, Daniel L. & Vermunt, Jeroen K. (03-03-2016). Relating Latent Class Membership to Continuous Distal Outcomes - Improving the LTB Approach and a Modified Three-Step Implementation. Structural Equation Modeling, 23 (2), (pp. 278-289) (12 p.).
  2016 - Overige resultaten
Oberski, D.L. 21-10-2016 Recipient Nomination New Scientist "New Science talent award" University of Amsterdam
  2015 - Wetenschappelijke publicaties
Meyers, Maria Christina, van Woerkom, Marianne, de Reuver, Renee S M, Bakk, Zsuzsa & Oberski, Daniel L. (2015). Enhancing Psychological Capital and Personal Growth Initiative - Working on Strengths or Deficiencies. Journal of Counseling Psychology, 62 (1), (pp. 50-62) (13 p.).
Oberski, Daniel L., Vermunt, Jeroen K. & Moors, Guy B D (01-10-2015). Evaluating Measurement Invariance in Categorical Data Latent Variable Models with the EPC-Interest. Political Analysis, 23 (4), (pp. 550-563) (14 p.).
Cieciuch, Jan, Davidov, Eldad, Oberski, Daniel L. & Algesheimer, René (01-12-2015). Testing for measurement invariance by detecting local misspecification and an illustration across online and paper-and-pencil samples. European Political Science, 14 (4), (pp. 521-538) (18 p.).
Oberski, Daniel L., Hagenaars, Jacques A. P. & Saris, Willem E. (2015). The Latent Class Multitrait-Multimethod Model. Psychological Methods, 20 (4), (pp. 422-443).
Oberski, D. L. & Vermunt, J. K. (2015). The relationship between cub and loglinear models with latent variables. Electronic Journal of Applied Statistical Analysis, 8 (3), (pp. 368-377) (8 p.).
  2014 - Wetenschappelijke publicaties
Oberski, Daniel L. (2014). Evaluating Sensitivity of Parameters of Interest to Measurement Invariance in Latent Variable Models. Political Analysis, 22 (1), (pp. 45-60).
Oberski, Daniel (2014). lavaan.survey: An R Package for Complex Survey Analysis of Structural Equation Models. Journal of Statistical Software, 57 (1), (pp. 1-27).
Bakk, Zsuzsa, Oberski, Daniel L. & Vermunt, Jeroen K. (2014). Relating Latent Class Assignments to External Variables: Standard Errors for Correct Inference. Political Analysis, 22 (4), (pp. 520-540).
  2013 - Wetenschappelijke publicaties
Oberski, Daniel L. & Vermunt, Jeroen K. (2013). A Model-Based Approach to Goodness-of-Fit Evaluation in Item Response Theory. Measurement: Journal of the International Measurement Confederation, 11 (3), (pp. 117-122) (6 p.).
Oberski, Daniel L., van Kollenburg, Geert H. & Vermunt, Jeroen K. (2013). A Monte Carlo evaluation of three methods to detect local dependence in binary data latent class models. Advances in Data Analysis and Classification, 7 (3), (pp. 267-279).
Oberski, Daniel L. & Satorra, Albert (01-07-2013). Measurement Error Models With Uncertainty About the Error Variance. Structural Equation Modeling, 20 (3), (pp. 409-428).
  2012 - Wetenschappelijke publicaties
Gallego, Aina & Oberski, Daniel (2012). Personality and Political Participation: The Mediation Hypothesis. Political Behavior, 34 (3), (pp. 425-451).

This is a non-exhaustive list of peer-reviewed journal articles only. For my full list of publications, preprints, and reproduction materials, please see http://daob.nl/publications

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Gegenereerd op 2018-08-15 01:55:37
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dr. D.L. Oberski Contactgegevens
Sjoerd Groenmangebouw

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Telefoonnummer direct 030 253 9075
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Gegenereerd op 2018-08-15 01:55:37
Laatst bijgewerkt op 16-04-2018