University of Amsterdam
Department of Psychology
PO box 15906
1001 NK Amsterdam
The Netherlands
Phone: +31205256584
E-Mail: D [dot] Molenaar [at] uva [dot] nl
Abstract
Dylan Molenaar is an assistant professor at the University of
Amsterdam, The Netherlands. His main research interests are psychometrics,
measurement, latent variable models, and test theory. He has published on
various topics related to psychometrics, including:
measurement invariance, factor analysis, item response theory, and latent
class modeling. This research has resulted in various international peer
reviewed journal articles in psychometrics and statistics journals like
‘Psychometrika’, ‘Structural Equation Modeling’, ‘Multivariate Behavior
Research’, and ‘British Journal of Mathematical and Statistical Psychology’.
He is the recipient of the 2013 best dissertation award and the 2019 early
career award by the Psychometric Society. He is associate editor of the
journal “Psychometrika” and member of the editorial boards of the journals
“Journal of Educational and Behavioral Statistics”, “Intelligence”, the
“Psychological and Educational Measurement” section of the open access
journal “Pysch”, and the proceedings of the Psychometric Society. |
Molenaar
[noun]: Miller (ENG), Molinero (SP), Müller (GER), Meunier (FR),
Mugnaio (IT)
Please find my papers below. Some papers include R, Mx, Mplus, OpenBUGS,
Rstan,
or LatentGOLD scripts.
Last updated 28 Oct 2022
Response and
Response Time Modeling
Becker, B., van Rijn, P., Molenaar, D., & Debeer, D. (2022). Item Order and Speededness: Implications for
Test Fairness in Higher Educational High-Stakes Testing. Assessment and
Evaluation in Higher Education, 47, 1030-1042.
Molenaar, D., Rózsa, S.,
& Kõ, N. (2021). Modeling Asymmetry in the Time-Distance Relation of
Ordinal Personality Items. Applied
Psychological Measurement, 45,
178-194. OpenBUGS-code
Kuijpers, R.E., Visser, I., & Molenaar,
D. (2011). Testing the Within-State Distribution in Mixture Models for
Responses and Response Times. Journal of
Educational and Behavioral Statistics, 46, 348-373. PDF
Tamimy, Z., Rózsa, S., Kõ, N., & Molenaar,
D. (2020). A Practical Cross-Sectional Framework to Contextual Reactivity
in Personality: Response Times as Indicators of Reactivity to Contextual Cues. Psych, 2(4), 253-268. PDF | LatentGOLD-scripts
Molenaar, D., & Schnipke, D.
(forthcoming). Item response time modeling. In: J. Weiner & S. Sireci
(Eds.), Guidelines for technical based
assessment. International Testing Commission and Association of Test
Publishers
Molenaar, D., & Van Rijn, P.
(forthcoming). Modeling Item Responses with Response Times as Collateral
Information in Large-Scale Educational Assessments. In: L. Khorramdel, M. von
Davier, & K. Yamamoto (Eds.), Innovative
Computer Based International Large-Scale Assessments. Springer.
Molenaar, D., Rósza, S., &
Bolsinova, M. (2019). A Heteroscedastic Hidden Markov Mixture Model for
Responses and Categorized Response Times. Behavior
Research Methods, 51, 676-696. PDF
Bolsinova,
M., & Molenaar, D. (2018).
Modeling nonlinear conditional dependence between response time and accuracy. Frontiers in Psychology: Quantitative
Psychology and Measurement, 9,
1525. PDF
Molenaar, D., & De Boeck, P.
(2018). Response Mixture Modeling: Accounting for Heterogeneity in Item
Characteristics across Response Times. Psychometrika, 83, 279-297. PDF | OpenBUGS-script
Molenaar, D., Bolsinova, M., &
Vermunt, J.K. (2018). A Semi-Parametric Within-Subject Mixture Approach to the Analyses of
Responses and Response Times. British
Journal of Mathematical and Statistical Psychology, 71, 205-228. PDF | LatentGOLD-script
Molenaar, D., & Visser, I. (Ed.) (2017). Cognitive and psychometric
modelling of responses and response times [special issue]. British
Journal of Mathematical and Statistical Psychology, 70(2),
185-186. Editorial (pdf) | Full
special issue
Molenaar, D., & Bolsinova, M. (2017). A heteroscedastic generalized
linear model with a non‐normal speed factor for responses and response
times. British Journal of Mathematical and Statistical Psychology, 70(2),
297-316. PDF | Mplus code + documentation
Bolsinova, M.,
Tijmstra, J., & Molenaar, D.
(2017). Response moderation models for conditional dependence between response
time and response accuracy. British Journal of Mathematical and
Statistical Psychology, 70(2), 257-279. PDF
Bolsinova, M., Tijmstra, J., Molenaar, D., & De Boeck, P.
(2017). Conditional dependence between response time and accuracy: An overview
of its possible sources and directions for distinguishing between them. Frontiers in psychology, 8. PDF
Molenaar,
D., Bolsinova, M., Rozsa, S., & De
Boeck, P. (2016). Response Mixture Modeling of Intraindividual Differences in
Responses and Response Times to the Hungarian WISC-IV Block Design Test. Journal of
Intelligence, 4, 10. PDF | OpenBUGS-scripts
Molenaar, D., Oberski, D.,
Vermunt, J.K., De Boeck, P. (2016). Hidden Markov IRT Models for Responses and Response Times. Multivariate Behavioral Research, 51, 606-626. PDF | LatentGOLD-scripts
Tuerlinckx, F., Molenaar, D., & van der Maas, H.L.J. (2016).
Molenaar, D. (2015). The value of response times in item response
modeling. Measurement: Interdisciplinary
Research and Perspectives, 13, 177-181. PDF
Molenaar, D., Tuerlinckx, F., & van der Maas, H.L.J. (2015).
A Bivariate Generalized Linear Item Response Theory Modeling Framework to
the Analysis of Responses and Response Times. Multivariate Behavioral Research, 50, 56-74. PDF | Scripts
Molenaar, D., Tuerlinckx, F., & van der Maas, H.L.J. (2015).
A Generalized Linear Factor Model Approach to the Hierarchical Framework
for Responses and Response Times. British Journal of Mathematical and
Statistical Psychology, 68, 197-219.
PDF
van der Maas, H.L.J., Molenaar, D., Maris, G., Kievit,
R.A., & Borsboom, D. (2011). Cognitive Psychology Meets Psychometric
Theory: On the Relation Between Process Models for Decision Making and Latent
Variable Models for Individual Differences. Psychological Review, 118, 339-356.
PDF
| Scripts
Moderated, Non-linear, Non-Normal, and/or
Heteroscedastic Latent Variable Modeling
Molenaar, D., Cúri, M., & Bazán, J.L. (in press). Zero and One Inflated Item
Response Theory Models for Bounded Continuous Data. Journal of Educational
and Behavioral Statistics. R-code
Kolbe, L., Molenaar, D., Jak, S., &
Jorgensen, T. D. (in press). Assessing Measurement Invariance with Moderated
Nonlinear Factor Analysis Using the R Package OpenMx. Psychological Methods.
Molenaar,
D. (2021). A Flexible Moderated Factor
Analysis Approach to Test for Measurement Invariance across a Continuous
Variable. Psychological Methods, 26, 660–679. R-code
Kolbe, L., Jorgensen, T. D., & Molenaar,
D. (2021). The impact of
unmodeled heteroscedasticity on assessing measurement invariance in
single-group models. Structural Equation
Modeling: A Multidisciplinary Journal,
28, 82-98. PDF
Bolsinova, M., & Molenaar, D.
(2019). Nonlinear indicator-level moderation in latent variable models. Multivariate Behavioral Research, 54, 62-84. PDF
Molenaar, D., &
Dolan, C.V. (2018). Non-Normality in Latent Trait Modeling. In P. Irwing, T.
Booth, D.J. Hughes (Eds). Wiley Blackwell Handbook of Psychometric Testing. UK: John Wiley &
Sons Ltd.
De
Korte, J., Dolan, C., Lubke, G., & Molenaar, D. (2017). Studying the strength of prediction using
indirect mixture modeling: non-linear latent regression with heteroscedastic
residuals. Structural Equation Modeling,
24, 301-313. PDF | OpenMx
scripts
Molenaar, D., Kő, N., Rózsa, S., & Mészáros, A. (2017). Differentiation of
cognitive abilities in the WAIS-IV at the item level. Intelligence, 65, 48-59. PDF | Mplus-script
Murray, A.L., Molenaar, D., Johnson, W., & Krueger, B. (2016). Dependence of
gene-by-environment interactions (GxE) on scaling: Comparing the use of sum
scores and IRT scores of the phenotype in tests of GxE. Behavior Genetics,
4, 552–572. PDF
Molenaar, D., Middeldorp, C.M., Willemsen, G., Ligthart, L.,
Nivard, M.G., & Boomsma, D.I. (2016).
Evidence for Gender-dependent Genotype by Environment Interaction in
Adult Depression. Behavior Genetics, 46,
59-71. PDF
Molenaar, D., Middeldorp,
C., Beijsterveldt, T., & Boomsma, D. I. (2015). Analysis of Behavioral and Emotional Problems in Children Highlights the
Role of Genotype× Environment Interaction. Child
development, 86, 1999-2016. PDF
Molenaar, D., & Dolan, C. V.
(2014). Testing systematic genotype by environment interactions using item
level data. Behavior genetics, 44, 212-231. PDF
Molenaar, D., van der Sluis, S.,
Boomsma, D.I., Haworth, C.M.A, Hewitt, J.K., Plomin, R., Wright, M.J., &
Dolan, C.V. (2013). Genotype by
Environment Interactions in Cognitive Ability Tested in 14 Different Studies. Behavior
Genetics, 43, 208-219. PDF
Molenaar,
D., Dolan,
C.V., & de Boeck, P. (2012). The Heteroscedastic Graded Response Model with
a Skewed Latent Trait: Testing Statistical and Substantive Hypotheses related
to Skewed Item Category Functions. Psychometrika
77, 455-478.
PDF | Mx code
Molenaar, D., & Dolan, C.V., (2012). Substantively
Motivated Extensions of the Traditional Latent Trait Model. Netherlands
Journal of Psychology, 67, 48-57. PDF
Molenaar, D. , van der Sluis, S., Boomsma, D.I., & Dolan,
C.V. (2012). Detecting Specific Genotype by Environment Interaction
using Marginal Maximum Likelihood Estimation in the Classical Twin Design. Behavior Genetics, 42, 483-499. PDF | Mx code | Univariate application
Molenaar, D., Dolan, C.V., &
van der Maas, H.L.J. (2011). Modeling ability differentiation in the
second-order factor model. Structural Equation
Modeling, 18, 578-594.
PDF
Molenaar, D., Dolan, C.V.,
Wicherts, J.M., & van der Maas, H.L.J. (2010). Modeling Differentiation of Cognitive Abilities within the Higher-Order
Factor Model using Moderated Factor Analysis. Intelligence, 38, 611-624. PDF | Mx code
Molenaar, D.,
Dolan, C.V., & Verhelst, N.D. (2010). Testing and modeling non-normality within the one
factor model. British Journal of
Mathematical and Statistical Psychology, 63, 293-317. PDF | Mx code
Molenaar,
D. &
Verhelst, N.D. (2007). Accounting for non-normality in latent regression models
using a cumulative normal selection function. Measurement and Research Department Reports, 3. Arnhem: Cito. PDF
Misc. Topics
Breit, M., Brunner, M., Molenaar,
D., & Preckel, F. (in press). Differentiation Hypotheses of
Intelligence: A Systematic Review of the Empirical Evidence and an Agenda for
Future Research. Psychological Bulletin.
Molenaar, D. (forthcoming). A factor analysis approach to item-level change score reliability.
In: A. van der Ark, W. Emons, & R. Meijer (Eds.), Practical measurement:
Essays on Contemporary Psychometrics. Springer
Junker,
T.L., Bakker, A.B., Derks, D., & Molenaar, D.
(in press). Agile Work
Practices: Measurement and Mechanisms. European Journal of Work and
Organizational Psychology.
Francken, J., Beerendonk, L., Molenaar, D.,
Fahrenfort, J., Kiverstein, J., Seth, A., & van Gaal, S. (in press). An academic survey
on theoretical foundations, common assumptions and the
current state of consciousness science. Neuroscience of Consciousness.
Pronk, T., Molenaar, D., Wiers, R.D., & Murre, J. (2022). Methods to Split
Cognitive Task Data for Estimating Split-Half Reliability: A Comprehensive
Review and a Systematic Assessment. Psychonomic Bulletin and
Review, 29, 44-54
Klein Haneveld, E., Molenaar, D.,
de Vogel, V., Smid, W., & Kamphuis, J.H. (2022). Do we Hold Males and
Females to the Same Standard? A Measurement Invariance Study on the Psychopathy
Checklist-Revised. Journal of Personality Assessment, 104, 368-379.
Molenaar,
D., Uluman, M., Tavşancıl, E., & De
Boeck, P. (2021). The Hierarchical Rater Thresholds Model for Multiple Raters
and Multiple Items. Open Education
Studies, 3, 33-48. R-code
Jovanović, V., Molenaar, D.,
Gavrilov Jerković, V., & Lazić, M. (2021). Positive expectancies and
subjective well-being: A prospective study among undergraduates in Serbia. Journal of Happiness Studies, 22, 1239-1258.
PDF
Molenaar, D., (in press). Review of Handbook of Item Response Theory,
Volume II: Statistical Tools. Journal of
Educational and Behavioral Statistics.
Jovanović, V., Lazić, M., Gavrilov-Jerković, V., & Molenaar, D. (2020). The Scale of Positive and Negative Experience
(SPANE): Evaluation of measurement invariance and convergent and discriminant
validity. European
Journal of Psychological Assessment, 36, 694–704.
Kovacs, K., Molenaar, D., &
Conway, A.R.A. (2019). The domain specificity of working memory is a matter of
ability. Journal of Memory and Language,
109, 104048. PDF
Xenidou-Dervou, I., Molenaar,
D., Ansari, D., van der Schoot, M., & van Lieshout, E. C. (2017).
Nonsymbolic and symbolic magnitude comparison skills as longitudinal predictors
of mathematical achievement. Learning and Instruction, 50,
1-13. PDF
Booth, T., Murray, A.L., &
Molenaar, D. (2016). Personality differentiation by cognitive ability: An
application of the moderated factor model. Personality
and Individual Differences, 100,
73-78. PDF
Molenaar, D. (2016). On the Distortion of Model fit in Comparing
the Bifactor Model and the Higher-Order Factor Model. Intelligence,
Molenaar, D. (2015). Intelligence tests. The Blackwell Encyclopedia of Race, Ethnicity and Nationalism. DOI:
10.1002/9781118663202.wberen544
Molenaar, D., & Borsboom, D. (2013). The Formalization of
Fairness: Issues in Testing for Measurement Invariance Using Subtest Scores. Educational research and evaluation, 2, 223-244. PDF
Wicherts, J.M., Bakker, M.,
Visch, V., Tan, E.S.H., & Molenaar, D. (2010). The emotional and cognitive effect of immersion in film viewing. Cognition & Emotion, 24, 1439-1445. PDF
Topper, M., Molenaar, D., Emmelkamp, P.M.G., & Ehring, T. (2014).
Are rumination and worry two sides of the same coin? A structural equation
modelling approach. Journal of
Experimental Psychopathology, 5, 363-381. PDF
Matzke, D., Dolan, C.V., & Molenaar, D. (2010). The issue of power in the identification of g with lower-order
factors. Intelligence, 38, 336-344. PDF
Molenaar, D., Dolan, C.V.,
& Wicherts, J.M. (2009). The power to detect sex differences in IQ test
scores using multi-group covariance and mean structure analysis. Intelligence, 37, 396-404. PDF
Wicherts, J.M., Borsboom, D., Kats, J., & Molenaar, D. (2006). The poor
availability of psychological research data for reanalysis. American
Psychologist, 61, 726-728. PDF
Proceedings of
the Psychometric Society
Wiberg, M., Molenaar, D., González, J., Kim,
K.S., & Hwang, H. (Eds.). (forthcoming). Quantitative Psychology: The 87nd Annual Meeting of the Psychometric Society, Bologna,
Italy, 2022. Springer.
Wiberg, M., Molenaar, D., González, J., Kim, K.S., & Hwang, H.
(Eds.). (2022). Quantitative Psychology: The 86nd Annual Meeting of the Psychometric Society Virtual,
2021. Springer. LINK
Wiberg, M., Molenaar, D., González, J., Bockenholt, U., & Kim, K.S.
(Eds.). (2021). Quantitative Psychology: The 85nd Annual Meeting of the Psychometric Society Virtual,
2020. Springer. LINK
Wiberg, M., Molenaar, D., González, J., Bockenholt, U., & Kim, K.S.
(Eds.). (2020). Quantitative Psychology: The 84nd Annual Meeting of the Psychometric Society, Santiago de
Chile, Chile, 2019. Springer. LINK
Wiberg, M., Culpepper, S., Janssen, R., González, J., & Molenaar, D.
(Eds.). (2019). Quantitative Psychology: The 83rd Annual
Meeting of the Psychometric Society, New York, NY, 2018. Springer. LINK
Wiberg, M., Culpepper, S., Janssen, R., González, J., & Molenaar, D.
(Eds.). (2018). Quantitative Psychology: The 82nd Annual
Meeting of the Psychometric Society, Zurich, Switzerland, 2017. Springer. LINK
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