Publications

Peer reviewed journal articles

  1. Kern, C., Klausch, T., & Kreuter, F. (2019). Tree-based Machine Learning Methods for Survey Research. Survey Research Methods, 13(1), 73–93.
  2. Schuller, W., Terwee, C. B., Klausch, T., Roorda, L. D., Rohrich, D. C., Ostelo, R. W., … De, H. V. (2019). Validation of the Dutch-Flemish PROMIS Pain Interference Item Bank in Patients With Musculoskeletal Complaints. Spine, 44(6), 411–419.
  3. Bálint, K., Klausch, T., & Pólya, T. (2018). Watching closely: Shot scale influences theory of mind response in visual narratives. Journal of Media Psychology: Theories, Methods, and Applications, 30(3), 150–159.
  4. Crins, M. H. P., Wees, P. J. van der, Klausch, T., Dulmen, S. A. van, Roorda, L. D., & Terwee, C. B. (2018). Psychometric properties of the PROMIS Physical Function item bank in patients receiving physical therapy. PLOS ONE, 13(2), e0192187.
  5. Hartman, L., Rasch, L. A., Klausch, T., Bijlsma, H. W. J., Christensen, R., Smulders, Y. M., …, Boers, M. (2018). Harm, benefit and costs associated with low-dose glucocorticoids added to the treatment strategies for rheumatoid arthritis in elderly patients (GLORIA trial): study protocol for a randomised controlled trial. Trials, 19(1), 67.
  6. Crins, M. H. P., Terwee, C. B., Klausch, T., Smits, N., de Vet, H. C. W., Westhovens, R., …, Roorda, L. D. (2017). The Dutch–Flemish PROMIS Physical Function item bank exhibited strong psychometric properties in patients with chronic pain. Journal of Clinical Epidemiology, 87, 47–58.
  7. Klausch, T., Schouten, B., Buelens, B., & Van Den Brakel, J. (2017). Adjusting Measurement Bias in Sequential Mixed-Mode Surveys Using Re-Interview Data. Journal of Survey Statistics and Methodology, 5(4), 409–432.
  8. Klausch, T., Schouten, B., & Hox, J. J. (2017). Evaluating Bias of Sequential Mixed-mode Designs Against Benchmark Surveys. Sociological Methods & Research, 46(3), 456–489.
  9. Klausch, T., Hox, J., & Schouten, B. (2015). Selection Error in Single- and Mixed-Mode Surveys of the Dutch General Population. Journal of the Royal Statistical Society: Series A (Statistics in Society), 178(4), 945-961.
  10. Klausch, T., Hox, J., & Schouten, B. (2013). Measurement Effects of Survey Mode on the Equivalence of Attitudinal Rating Scale Questions. Sociological Methods and Research, 42(3), 227-263.
  11. Schouten, B., van den Brakel, J., Buelens, B., van der Laan, J., Burger, J., & Klausch, T. (2013). Disentangling mode-specific selection and measurement bias in social surveys. Social Science Research, 42(6), 1555-1570.

Papers completed (under review / to be submitted)

  1. Klausch, T., van de Ven, P., van de Brug, T., van de Wiel, M. A., & Berkhof, J. (2018). Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data. Available from: https://arxiv.org/abs/1809.06679v2.
  2. Klausch, T., Nauta, I., van de Ven, P., et. al. , Berkhof, J., & Brakenhoff, R. (2019). The efficacy of platinum-based chemotherapy in OPSCC: Causal modeling of real-world multicenter cohort data.
  3. Schouten, B., Klausch, T., Buelens, B. & van den Brakel, J. (2019). A cost-benefit analysis of re-interview designs for mode-specific measurement bias: A case study for the Dutch Health survey and Labour Force survey.
  4. Jongeneel, G., Klausch, T., …, & Coupe, V. (2019). Estimating adjuvant treatment effects in stage II colon cancer: comparing the synthesis of RCT data to real world data.
  5. Jager, J., Maarse, F., Klausch, T., et al. (2019). Wound dehiscences following pre-implant bone augmentation with autogenous iliac crest bone grafts: A retrospective cohort study (2019). (Minor revisions at International Journal of Oral Implantology).

Books and articles in edited books

  1. Klausch, T. (2014). Informed Design of Mixed-Mode Surveys: Evaluating Mode Effects on Measurement and Selection Error. Unpublished PhD thesis, Utrecht University, Utrecht.
  2. Roberts, A., de Leeuw E., Hox, J., Klausch, T., de Jongh, A. (2013). Leuker kunnen wij het wel maken. Online vragenlijst design: standaard matrix of scrollmatrix (We can actually make it nicer. Online questionnaire design: standard matrix or scrollmatrix). In MOA (ed.), Jaarboek MarktOnderzoekAssociatie 2013(pp. 133-148). Amsterdam: MOA.
  3. Roberts, A., de Leeuw, E., Hox, J., Klausch, T., & de Jongh, A. (2013). Pret met panels (Fun with panels). In MOA (ed.), Insights in Marketing Intelligence: Highlights en trends uit het MOA Jaarboek 2013 (pp. 44-46). Amsterdam: MOA.
  4. De Vreese, C. & Klausch, T. (2011). The Salience of Frames and their Effects on the Support for CFSP and Supranational Policy Allocation. In K. Oppermann & H. Viehring (eds.), Issue Salience in International Politics (pp. 118-136). Abingdon: Routledge.

Discussion papers and deliverables

  1. Klausch, T., van de Ven, P., & Berkhof, J. (2018). Deliverable D4.1: The BD2Decide survival model recalibration, validation and prognostic tool package. Brussels: European Commission.
  2. Klausch, T., Schouten, B., & Hox, J. (2014). The Use of Within-Subject Experiments for Estimating Measurement Effects in Mixed-Mode Surveys (Discussion Paper No. 2014-06). The Hague, The Netherlands: Statistics Netherlands.
  3. Klausch, T., Hox, J. , & Schouten, B. (2013). Assessing the mode-dependency of sample selectivity across the survey response process (Discussion Paper No. 2013-03). The Hague, The Netherlands: Statistics Netherlands.
  4. Buelens, B., van der Laan, J., Schouten, B., van den Brakel, J., & Klausch, T. (2012). Disentangling mode-specific selection and measurement bias in social surveys (Discussion paper No. 201211). The Hague, The Netherlands: Statistics Netherlands.

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