1. 2018
  2. Meijer, R. R., & Tendeiro, J. N. (2018). Unidimensional item response theory. In P. Irwing, T. Booth, & D. J. Hugh (Eds.), The Wiley handbook of psychometric testing : A multidisciplinary reference on survey, scale and test development (pp. 413-433). WILEY. https://doi.org/10.1002/9781118489772.ch15
  3. Timmerman, M. E., Lorenzo-Seva, U., & Ceulemans, E. (2018). The Number of Factors Problem. In The Wiley Handbook of Psychometric Testing: A Multidisciplinary Reference on Survey, Scale and Test Development (pp. 305-324). John Wiley & Sons. https://doi.org/10.1002/9781118489772.ch11
  4. van Ravenzwaaij, D. (2018). In Vivo: MCMC: A Clever Way to Run the Numbers. In S. Farrell, & S. Lewandowsky (Eds.), Computational Modeling of Cognition and Behaviour (pp. 170-171). Cambridge University Press. https://doi.org/10.1017/CBO9781316272503.008
  5. 2017
  6. Albers, C., Gower, J., & Kiers, H. (2017). Rank properties for centred three-way arrays. In F. Mola, C. Conversano, & M. Vichi (Eds.), Classification, (Big) Data Analysis and Statistical Learning (Studies in Classification, Data Analysis and Knowledge Organization). Springer.
  7. 2016
  8. Sense, F., Meijer, R. R., & van Rijn, H. (2016). On the Link between Fact Learning and General Cognitive Ability. In A. Papafragou, D. Grodner, D. Mirman, & J. C. Trueswell (Eds.), Proceedings of the 38th Annual Conference of the Cognitive Science Society Austin, TX: Cognitive Science Society.
  9. 2015
  10. Sense, F., Behrens, F., Meijer, R., & van Rijn, H. (2015). Stability of individual parameters in a model of optimal fact learning. In N. A. Taatgen, M. K. van Vugt, J. P. Borst, & K. Mehlhorn (Eds.), Proceedings of the 13th International Conference on Cognitive Modeling (pp. 136-141). Groningen: University of Groningen.
  11. Boevé, A., Bronkhorst, L., Endedijk, M. D., & Meijer, P. (2015). Tackling methodological challenges to gain new insight into the complexity of student teacher learning in a dual teacher education program. In V. Donche, S. De Mayer, D. Gijbels, & H. van den Bergh (Eds.), Methodological Challenges in Research on Student Learning (pp. 27-53). (Methodology and Statistics Series). Antwerp-Apeldoorn: Garant Publishers.
  12. 2014
  13. Meijer, R., Tendeiro, J., & Wanders, R. (2014). The use of nonparametric item response theory to explore data quality. In: S. P. Reise & D. Revicki (Eds.). Handbook of item response theory modeling: Applications to typical performance assessment. In S. P. Reise & D. Revicki (Eds.). Handbook of item response theory modeling: Applications to typical performance assessment. (pp. 85-110). Routledge.
  14. Stegeman, A. (2014). Nonexistence of best low-rank approximations for real-valued three-way arrays and what to do about it. In 21st International Symposium on Mathematical Theory of Networks and Systems (pp. 954-957)
  15. de Raad, B. (2014). Willem Karel Bernard (WKB) Hofstee, wetenschapsbeoefenaar. In H. Amsing, & M. van Essen (Eds.), Over professoren: Een halve eeuw psychologie, pedagogiek en sociologie aan de Rijksuniversiteit Groningen (pp. 78-103). Assen: Koninklijke Van Gorcum.
  16. 2013
  17. Visser, L., van der Meulen, B., Ruiter, S., Timmerman, M., & Ruijssenaars, W. (2013). The Bayley-III accommodated for motor and/or visual impairment: “Low motor/vision version”. In L. Visser, & B. F. van der Meulen (Eds.), New developments in the assessment of young children with the Bayley-III
  18. 2011
  19. Waninge, A., Van der Putten, A. A. J., Stewart, R. E., Steenbergen, B., Van Wijck, R., & Van der Schans, C. P. (2011). Heart rate pattern as indicator of physical activity in persons with profound intellectual, and multiple disabilities. In A. Waninge (Ed.), Measuring physical fitness in persons with severe/profound intellectual and multiple disabilities (pp. 121 - 137). Amersfoort: Wilco.
  20. 2010
  21. Rouder, J. N., Speckman, P., Steinley, D., Pratte, M. S., & Morey, R. D. (2010). A resampling test of shape invariance across distributions. In S. Kolenikov, D. Steinley, & L. Thombs (Eds.), Current methodological developments of statistics in the social sciences (pp. 159-174). New York: Wiley.
  22. Ruiter, S. A. J., Visser, L., Van der Meulen, B. F., Timmerman, M. E., & Ruijssenaars, A. J. J. M. (2010). Adaptive developmental assessment of young children with cognitive and/or functional impairments. In E. J. Knorth, M. E. Kalverboer, & J. Knot-Dickscheit (Eds.), Inside out : how interventions in child and family care work : an international source book (pp. 589-592). (KOP-serie; No. 30). Antwerpen: Garant Publishers.
  23. Meijer, R. R., & Weekers, A. M. (2010). Appropriateness measurement: Person-fit. In P. Petersen, E. Baker, & B. McGaw (Eds.), International Encyclopedia of Education (pp. 15-19). Oxford: Elsevier.
  24. Meijer, R. R., & Van Krimpen-Stoop, E. M. L. A. (2010). Detecting person misfit in adaptive testing. In W. J. van der Linden, & C. A. W. Glas (Eds.), Elements of adaptive testing (pp. 315-329). New York: Springer.
  25. Timmerman, M. E., & Ceulemans, E. (2010). The generic subspace clustering model. In Y. Lechevallier, & G. Saporta (Eds.), Proceedings of COMPSTAT'2010 (pp. 359-368). Berlin: Springer.
  26. 2009
  27. Timmerman, M. E., Ceulemans, E., Lichtwarck-Aschoff, A., & Vansteelandt, K. (2009). Multilevel Simultaneous Component Analysis for studying intra-individual variability and inter-individual similarities. In J. Valsiner, P. C. M. Molenaar, M. C. D. P. Lyra, & N. Chaudhary (Eds.), Dynamic process methodology in the social and developmental sciences (pp. 291-318). New York: Springer.
  28. 2008
  29. Albers, C. (2008). Some quadratic optimisation problems in psychometrics. In K. Shigemasu, A. Okada, T. Imaizumi, & T. Hoshino (Eds.), New Trends in Psychometrics (pp. 1 - 6). Tokyo: Universal Academic Press.
  30. Gärtner, F. R., & Tellegen, P. J. (2008). The SON-R 5,5-17: An Accurate Test Instrument for Roma Children? A case study in Amsterdam, Bratislava and Košice. In D. Kopčanová (Ed.), Equal access to quality education for children from socially disadvantaged settings (pp. 81 - 97). Bratislava: Vudpap/Unesco.
  31. 2007
  32. Albers, C. J., Critchley, F., & Gower, J. C. (2007). Group Average Representations in Euclidean Distance Cones. In P. Brito (Ed.), Selected Contributions in Data Analysis and Classification: Studies in Classification, Data Analysis, and Knowledge Organization (pp. 445 - 454). Springer. https://doi.org/10.1007/978-3-540-73560-1_41
  33. Huisman, M. (2007). Multipele imputatie van ontbrekende scores. In A. E. Bronner, P. Dekker, E. de Leeuw, L. J. Paas, K. de Ruyter, A. Smidts, & J. E. Wieringa (Eds.), Ontwikkelingen in het marktonderzoek, Jaarboek 2007 MarktOnderzoekAssociatie (pp. 171 - 188). Haarlem: Spaar & Hout.
  34. Ten Berge, J. M. F., & Sočan, G. (2007). The set of feasible solutions for reliability and factor analysis. In S. Y. Lee (Ed.), Handbook of latent variable and related models (pp. 303-320). Amsterdam: Elsevier.
  35. 2006
  36. Van Wijck, R. (2006). Physical fitness status of people with intellectual disabilities. In Proceedings European Conference on Adapted Physical Activity (EUCAPA). Olomouc.
  37. Hoekstra, R., Kiers, H. A. L., Johnson, A., & Groenier, M. (2006). Problems when interpreting research results using only p-value and sample size. In A. Rosman, & B. Chance (Eds.), ICOTS7 conference proceedings (CD-Rom) Voorburg: International Statistical Institute.
  38. Kiers, H. A. L., & Groenen, P. J. F. (2006). Visualizing dependence of bootstrap confidence intervals for methods yielding spatial configurations. In S. Zani, A. Cerioli, M. Riani, & M. Vichi (Eds.), Data Analysis, Classification and the Forward Search: proceedings of the Meeting of the Classification and Data Analysis Group (CLADAG) of the Italian Statistical Society, University of Parma, June 6-8, 2005 (pp. 119-126). (Studies in Classifiction, Data Analysis, and Knowledge Organization). Berlin: Springer.
  39. 2005
  40. Groenen, P. J. F., Giaquinto, P., & Kiers, H. A. L. (2005). An improved majorization algorithm for robust procrustes analysis. In P. Monari, S. Mignani, A. Montanari, & M. Vichi (Eds.), New developments in classification and data analysis (pp. 151-158). (Studies in classification, data analysis, and knowledge organization). Berlin Heidelberg: Springer.
  41. Kiers, H. A. L. (2005). Bootstrap confidence intervals for three-way component methods. In C. Weigh, & W. Gaul (Eds.), Classification - the Ubiquitous challenge. (pp. 73-84). (Studies in Classification, Data Analysis, and Knowledge Organization). Berlin: Springer.
  42. Tellegen, P. J., & Laros, J. A. (2005). Fair assessment of children from cultural minorities: A description of the SON-R Non-verbal intelligence tests. In Kopcanova (Ed.), Quality education for children from socially disadvantaged settings (pp. 55 - 71). Bratislava: Vudpap/Unesco.
  43. Huisman, M., & van Duijn, M. A. J. (2005). Software for social network analysis. In P. J. Carrington, J. Scott, & S. Wasserman (Eds.), Models and methods in social network analysis (pp. 270 - 316). New York: Cambridge University Press.
  44. Ten Berge, J. M. F. (2005). Tau-equivalent and congeneric measurements. In R. K. Hambleton (Ed.), Encyclopedia of Statistics in Behavioral Science IV (pp. 1991 - 1994). New York: Wiley.
  45. 2004
  46. Kiers, HAL. (2004). Clustering all three modes of three-mode data: Computational possibilities and problems. In J. Antoch (Ed.), COMPSTAT Proceedings in Computational Statistics (pp. 303-313). HEIDELBERG: Physica.
  47. 2003
  48. van der Velden, M., & Kiers, H. A. L. (2003). An application of rotation in correspondence analysis. In H. Yanai, A. Okada, K. Shigemasu, Y. Kano, & JJ. Meulman (Eds.), New developments in Psychometrics: Proceedings of the international meeting of the Psychometric Society IMPS 2001 (pp. 471-478)
  49. Kiers, H. A. L. (2003). Some alternatives to PLS. In Atti del Convegno Intermedio della Società Italiana di Statistica "Analisi Statistica Multivariata per le Scienze Economico-Sociali, le Scienze Naturali e la Tecnologia": Napoli 9–11 giugno 2003 (pp. 171-182). Napoli: RCE Edizioni.
  50. Kiers, H. A. L. (2003). Uniqueness properties of three-way component models with offset terms. In H. Yanai, A. Okada, K. Shigemasu, Y. Kano, & JJ. Meulman (Eds.), New Developments in Psychometrics (pp. 355-362). Tokio: Springer.
  51. 2002
  52. Molenaar, W. (2002). Groups of Persons and Groups of Items in Nonparametric Item Response Theory. In H. Yanai, A. Okada, K. Shigemasu, Y. Kano, & JJ. Meulman (Eds.), New Developments in Psychometrics. (pp. 191 - 198). Tokio: Springer.
  53. Molenaar, W. (2002). Parametric and Nonparametric Item Response Theory Models in Health Related Quality of Life Measurement. In M. Mesbah, BF. Cole, & MLT. Lee (Eds.), Statistical Methods for Quality of Life Studies. Design Measurements and Analysis. Dordrecht: Kluwer Academic Publishers.
  54. 2001
  55. Huisman, M., & Molenaar, W. (2001). Imputation of missing scale data with item response models. In T. A. B. Snijders, A. Boomsma, & M. A. J. van Duijn (Eds.), Essays on Item Response Theory. Lecture Notes in Statistics, 157 (pp. 221 - 244). New York: Springer.
  56. Post, W. J., & van Duijn, M. A. J. (2001). Single-Peaked or Monotone Tracelines? On the Choice of an IRT Model for Scaling Data. In T. A. B. Snijders, A. Boomsma, & M. A. J. van Duijn (Eds.), Essays on Item Response Theory. Lecture Notes in Statistics, 157 (pp. 391 - 414). New York: Springer.
  57. Boomsma, A. (2001). The robustness of LISREL modeling revisted. In R. Cudeck, D. Sörbom, & S. du Toit (Eds.), Structural equation models: Present and Future. A Festschrift in honor of Karl Jöreskog. (pp. 139 - 168). Chicago: Scientific Software International.
  58. Boomsma, A., & Ostendorf, F. (2001). Trait structure - Abridged-circumplex versus hierarchical conceptions. In F. Ostendorf, F. M. Spinath, & R. Riemann (Eds.), Personality and Temperament: Genetics, Evolution, and Structure. (pp. 207 - 215). Berlin: Pabst Science Publishers.
  59. 2000
  60. Kiers, H. A. L., & Krzanowski, W. J. (2000). Projections Distinguishing Isolated Groups in Multivariate Data Spaces. In M. Schader, W. Gaul, & M. Opitz (Eds.), Data analysis. Scientific Modeling and Practical Application (pp. 207-218). Berlin-New York, etc.: Springer.
  61. Wittek, R., Hangyi, H., van Duijn, M. A. J., & Carroll, C. (2000). The Management of Durable Relations. In W. Raub, & J. Weesie (Eds.), Social Capital, third party gossip, and cooperation in organizations (pp. 100 - 101). Thela Thesis.
  62. 1999
  63. Molenaar, W. (1999). Assessing model fit in Item Response Theory. In M. Mesbah (Ed.), Actes du Séminaire du Labaratoire SABRES (Proceedings of the SABRES Laboratory Seminar) (pp. 169 - 175). South Brittany: University of Vannes.
  64. 1998
  65. Kiers, H. A. L. (1998). An overview of three-way analysis and some recent developments. In A. Rizzi, M. Vichi, & H. H. Bock (Eds.), Advances in data science and classification (pp. 593-602). Berlin-New York, etc.: Springer.
  66. Timmerman, M. E., & Kiers, H. A. L. (1998). Constrained three-way data analysis of multivariate longitudinal data. In Data Science, Classification and Related methods (pp. 307-310). Rome: Istituto Nazionale di Statistica.
  67. Molenaar, W. (1998). Mokken scaling as a source of inspiration. In H. Schijf, M. Fennema, & C. van der Eijk (Eds.), In search of structure: essays in social science and methodology (pp. 29 - 62). Amsterdam: Het Spinhuis.
  68. Kiers, H. A. L. (1998). Recent Developments in Three-Mode Factor Analysis: Constrained Three-Mode Factor Analysis and Core Rotations. In C. Hayashi, N. Ohsumi, K. Yajima, H. H. Bock, & Y. Baba (Eds.), Data Science, Classification and Related Methods (pp. 563-574). Berlin-New York, etc.: Springer.
  69. 1997
  70. Molenaar, W. (1997). Lenient or strict application of IRT with an eye on practical consequences. In J. Rost, & R. Langeheine (Eds.), Applications of latent trait and latent class models in the social sciences (pp. 38 - 49). Münster/New York: Waxmann Verlag.
  71. 1996
  72. Scheines, R. (1996). An introduction to Causal Inference. In S. Turner, & V. McKim (Eds.), . University of Notre Dame Press.
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