Photographer: onbekend

dr. L.J. (Lourens) Waldorp


  • Faculty of Social and Behavioural Sciences
  • Visiting address
    REC G
    Nieuwe Achtergracht 129  Room number: 0.33
  • Postal address:
    Postbus  15906
    1001 NK  Amsterdam
  • L.J.Waldorp@uva.nl
    T: 0205256420

Lourens Waldorp is assistent professor at the Department of Psychological Methods. His research concerns statistical hypothesis testing, especially in the neurosciences. For example, in fMRI the problem is to cope with thousends of multiple tests without declaring truely nonactive regions active.  In general, many topics in (multivariate) statistics are of interest, like (non)linear regression and asymptotic statistics.

Interests

  • graph (network) theory
  • graphical models
  • network discovery
  • mathematical statistics
  • applications to biophysical data
  • signal processing


Teaching

  • statistics for first year psychology and beta-gamma students
  • multivariate statistics
  • Network analysis
  • Model selection


Homepage

Publications

refereed journals

  • Waldorp, L.J. , Christoffels, I.K., and van de Ven, V. (2010) Effective connectivity of fMRI data using ancestral graph theory: Dealing with missing regions. NeuroImage,54 , 2695-2705.
  • Cramer, A. O. J., Waldorp, L. J. , van der Maas, H., & Borsboom, D. Comorbidity: A network perspective. Behavioral and Brain Sciences , (accepted).
  • Waldorp, L.J. (2009). Robust and unbiased variance of GLM coefficients for misspecified autocorrelation and hemodynamic response models in fMRI. International Journal of Biomedical Imaging Volume 2009, Article ID 723912.
  • Scholte, H. S., Ghebreab, S., Waldorp, L. , Smeulders, A. W. M., and Lamme, V. A. F. (2009). Brain responses strongly correlate with Weibull image statistics when processing natural images. Journal of Vision, 9(4):29, 1-15.
  • Weeda, W.D., Waldorp, L.J. , Christoffels, I.K., and Huizenga, H.M.. (2009) Activated region fitting:A robust high power method for fMRI analysis using parameterized regions of activation. Human Brain Mapping,30, 2595-2605.
  • Waldorp, L.J. (2008). Brazzale, A. R., Davison, A. C., and Reid, N.: Applied asymptotics: Case Studies in Small Sample Statistics (book review). Biometrics, 64(2) , p. 660.
  • Waldorp, L.J. , Huizenga, H.M., Grasman, R.P.P.P., and Molenaar, P.C.M. (2006). Hypothesis testing in distributed source models for EEG and MEG data. Human Brain Mapping, 27(2) , p. 114-128.
  • Waldorp, L.J. , Grasman, R.P.P.P., and Huizenga, H.M. (2006). Goodness-of-fit and confidence intervals for approximate models. Journal of Mathematical Psychology, 50 , p. 203-213.
  • Waldorp, L.J. , Huizenga, H.M., and Grasman, R.P.P.P. (2005). The Wald test and Cramer-Rao bound in electromagnetic source analysis. IEEE Transactions on Signal Processing, 53(9) , p. 3427-3435.
  • Waldorp, L.J. , Huizenga, H.M., Nehorai,A., Grasman, R.P.P.P., and Molenaar, P.C.M. (2005). Model selection in spatio-temporal electromagnetic source analysis. IEEE Transactions on Biomedical Engineering, 52(3) , p. 414-220.
  • Grasman, R.P.P.P., Huizenga, H.M. Waldorp, L.J. , Molenaar, P.C.M., and Bocker, K.B.E. (2005). Stochastic maximum likelihood mean and cross spectrum structure modelling in neuromagnetic source estimation. Digital Signal Processing, 15(1) , p. 5672.
  • Grasman, R.P.P.P., Huizenga, H.M. Waldorp, L.J. , Bocker, K.B.E., and Molenaar, P.C.M. (2004). Frequency Domain Simultaneous Source and Source Coherence Estimation With an Application to MEG. IEEE Transactions on Biomedical Engineering, 51(1) , p. 4555.
  • Christoffels, I.K., De Groot, A.M.B., and Waldorp, L.J. (2003). Basic skills in a complex task: A graphical model relating memory and lexical retrieval to simultaneous interpreting. Bilingualism: Language and Cognition, 6(3) , p. 201-211.
  • Waldorp,L.J. , Huizenga, H.M., Grasman, R.P.P.P., Bocker, K.B.E., de Munck, J.C., and Molenaar, P.C.M. (2002). Model selection in electromagnetic source analysis with an application to VEFs. IEEE Transactions on Biomedical Engineering, 49 , p. 737-741.
  • Huizenga, H.M., de Munck, J.C., Waldorp, L.J. , and Grasman, R.P.P.P. (2002). Spatiotemporal EEG/MEG source analysis based on a parametric noise covariance model. IEEE Transactions on Biomedical Engineering 49(6) , p. 533-539.
  • de Munck, J.C., Huizenga, H.M., Waldorp, L.J. , and Heethaar, R.M. (2002). Estimating stationary dipoles from MEG/EEG data contaminated with spatially and temporally correlated background noise. IEEE Transactions on Signal Processing, 50(7) , p. 1565-1572.
  • Waldorp, L.J. , Huizenga, H.M., Dolan, C.V., and Molenaar, P.C.M. (2001). Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model. IEEE Transactions on Biomedical Engineering 48 , p. 737-741.
  • Phaf, R.H., Christoffels, I.K., Waldorp, L.J. , and den Dulk, P. (1998). Connectionist investigations of individual differences in stroop performance. Perceptual and Motor Skills 87 , p. 899-914.

proceedings
  • L.J. Waldorp , H.M. Huizenga, A. Nehorai, R.P.P.P. Grasman, and P.C.M. Molenaar (2004). Model selection in spatio-temporal electromagnetic source analysis. In: Biomag2004, Proc. 14th Int. Conf. on Biomagnetism , E. Halgren, S. Ahlfors, M. Hamalanen, D. Cohen eds. (Boston, Massachusetts, USA, 2004), p. 188-189.
  • L.J. Waldorp , H.M. Huizenga, R.P.P. Grasman, J.C. de Munck, K.B.E. Bocker, and P.C.M. Molenaar (2002). Model selection in electromagnetic source analysis. In: Biomag2002, Proc. 13th Int. Conf. on Biomagnetism , J. H. Nowak, J. Haueiesen, F. Gießler, R. Huonker eds. (Univ. of Jena, Jena, Germany, 2002), p. 807-809.
  • R.P.P.P. Grasman, L.J. Waldorp , H.M. Huizenga, K.B.E.Bocker, and P.C.M. Molenaar (2002). Frequency domain source and source coherence analysis. In: Biomag2002, Proc. 13th Int. Conf. on Biomagnetism , J. H. Nowak, J. Haueiesen, F. Gießler, R. Huonker eds. (Univ. of Jena, Jena, Germany, 2002), p. 751-753.
  • H.M. Huizenga, R.P.P. Grasman, L.J. Waldorp , J.C. de Munck, K.B.E. Bocker, and P.C.M. Molenaar (2002). Analysis of EEG/MEG sources and their lagged covariances. In: Biomag2002, Proc. 13th Int. Conf. on Biomagnetism , J. H. Nowak, J. Haueiesen, F. Gießler, R. Huonker eds. (Univ. of Jena, Jena, Germany, 2002), p. 825-828.
  • J.C. de Munck, F. Bijma, H.M. Huizenga, L.J. Waldorp , and R. Heethaar (2002). Spatial and temporal correlations in MEG/EEG background noise. In: Biomag2002, Proc. 13th Int. Conf. on Biomagnetism , J. H. Nowak, J. Haueiesen, F. Gießler, R. Huonker eds. (Univ. of Jena, Jena, Germany, 2002), p. 819-821.
  • K.B.E. Bocker, L.J. Waldorp , R.P.P. Grasman, J.C. de Munck, J.L. Kenemans, and H.M. Huizenga (2002). Estimating the number of sources in a VEF/MRI study. In: Biomag2002, Proc. 13th Int. Conf. on Biomagnetism , J. H. Nowak, J. Haueiesen, F. Gießler, R. Huonker eds. (Univ. of Jena, Jena, Germany, 2002), p. 454-456.
  • L.J. Waldorp , H.M. Huizenga, C.V. Dolan, R.P.P.P. Grasman, and P.C.M. Molenaar. (2000). Maximum likelihood estimation with a parametric noise covariance model for instantaneous and spatio-temporal electromagnetic source analysis. In: M. Viberg (ed.) Proceedings of the 2000 IEEE Sensor Array and Multichannel Signal Processing Workshop . Cambridge: Springer-Verlag.
  • L.J. Waldorp , H.M. Huizenga, R.P.P.P. Grasman, and P.C.M. Molenaar (2000). Model selection procedures in electromagnetic source analysis. In: Biomag2000, Proc. 12th Int. Conf. on Biomagnetism , J. Nenonen, R.J. Ilmoniemi, and T. Katila, eds. (Helsinki Univ. of Technology, Espoo, Finland, 2001), p. 693-696.
  • H.M. Huizenga, L.J. Waldorp , and R.P.P.P. Grasman (2000). Maximum likelihood spatiotemporal electromagnetic source analysis. In: Biomag2000, Proc. 12th Int. Conf. on Biomagnetism , J. Nenonen, R.J. Ilmoniemi, and T. Katila, eds. (Helsinki Univ. of Technology, Espoo, Finland, 2001), p. 721-724.
  • R.P.P.P. Grasman, H.M. Huizenga, P.C.M. Molenaar, and L.J. Waldorp . (2000). Electromagnetic source localization and interactions between neural generators. In: Biomag2000, Proc. 12th Int. Conf. on Biomagnetism , J. Nenonen, R.J. Ilmoniemi, and T. Katila, eds. (Helsinki Univ. of Technology, Espoo, Finland, 2001), pp. 738-741.
abstracts
  • Waldorp, L.J. , Christoffels, I.K., and Van de Ven, V. (2009). Modelling functional and effective connectivity simultaneously with possible unobserved areas in fMRI. Human Brain Mapping (in press).
  • L.J. Waldorp , R.P.P.P Grasman, W.D. Weeda, H.M. Huizenga (2006). Robust latency testing in fMRI. NeuroImage, S.
  • L.J. Waldorp , H.M. Huizenga, R.P.P.P. Grasman, and E. Formisano. Using the sandwich estimate for reliable covariance of coefficients and hypothesis testing in fMRI with temporally correlated residuals, NeuroImage, 26 , S41.
  • L.J. Waldorp , H.M. Huizenga, and P.C.M. Molenaar (2001). Goodness of fit measures in electromagnetic source analysis. (ISBET2000) Brain Topography , 13(3), p. 246.
  • H.M. Huizenga, L.J. Waldorp , and R.P.P.P. Grasman (2001). Maximum likelihood spatiotemporal source analysis. (ISBET2000) Brain Topography, 13(3) , p. 235.
  • J.C. de Munck, H.M. Huizenga, L.J. Waldorp , and R. Heethaar (2001). Estimating stationary dipoles from MEG/EEG data contaminated with spatially and temporally correlated background noise. NeuroImage, 13 (6) , S109.
  • L.J. Waldorp , C.V. Dolan, and H.M. Huizenga (2000). A parametric model of noise covariances for GLS electromagnetic source analysis. Journal of Psychophysiology, 14(4) , 266-267.

2018

  • Werner, M., Štulhofer, A., Waldorp, L., & Jurin, T. (2018). A Network Approach to Hypersexuality: Insights and Clinical Implications. Journal of Sexual Medicine, 15(3), 373-386. DOI: 10.1016/j.jsxm.2018.01.009  [details] 
  • Verschuere, B., van Ghesel Grothe, S., Waldorp, L., Watts, A. L., Lilienfeld, S. O., Edens, J. F., ... Noordhof, A. (2018). What features of psychopathy might be central? A network analysis of the psychopathy checklist-revised (PCL-R) in three large samples. Journal of Abnormal Psychology, 127(1), 51-65. DOI: 10.1037/abn0000315  [details] 
  • Haslbeck, J. M. B., & Waldorp, L. J. (2018). How well do network models predict observations? On the importance of predictability in network models. Behavior Research Methods, 50(2), 853-861. DOI: 10.3758/s13428-017-0910-x  [details] 
  • Jahfari, S., Ridderinkhof, K. R., Collins, A. G. E., Knapen, T. H. J., Waldorp, L. J., & Frank, M. J. (2018). Cross-task contributions of fronto-basal ganglia circuitry in response inhibition and conflict-induced slowing. Cerebral Cortex. DOI: 10.1093/cercor/bhy076 
  • Marsman, M., Borsboom, D., Kruis, J., Epskamp, S., van Bork, R., Waldorp, L. J., ... Maris, G. (2018). An introduction to network psychometrics: Relating ising network models to item response theory models. Multivariate Behavioral Research, 53(1), 15-35. DOI: 10.1080/00273171.2017.1379379  [details] 
  • van Bork, R., Rhemtulla, M., Waldorp, L. J., Kruis, J., Rezvanifar, S., & Borsboom, D. (submitted). Latent Variable Models and Networks: Statistical Equivalence and Testability. Multivariate Behavioral Research.
  • van Bork, R., Grasman, R. P. P. P., & Waldorp, L. J. (in press). Unidimensional factor models imply weaker partial correlations than zero-order correlations. Psychometrika.

2017

  • Dalege, J., Borsboom, D., van Harreveld, F., Waldorp, L. J., & van der Maas, H. L. J. (2017). Network Structure Explains the Impact of Attitudes on Voting Decisions. Scientific Reports, 7, [4909]. DOI: 10.1038/s41598-017-05048-y  [details] 
  • Marsman, M., Waldorp, L., & Maris, G. (2017). A note on large-scale logistic prediction: Using an approximate graphical model to deal with collinearity and missing data. Behaviormetrika, 44(2), 513-534. DOI: 10.1007/s41237-017-0024-x  [details] 
  • Epskamp, S., Waldorp, L. J., Mõttus, R., & Borsboom, D. (submitted). Discovering Psychological Dynamics: The Gaussian Graphical Model in Cross-sectional and Time-series Data. Multivariate Behavioral Research.
  • Haslbeck, J. M. B., Bringmann, L., & Waldorp, L. J. (submitted). How to estimate time-varying Vector Autoregressive Models? A comparison of two methods. Psychological Methods.
  • Haslbeck, J. M. B., & Waldorp, L. J. (submitted). mgm: Structure Estimation for Time-Varying Mixed Graphical Models in high-dimensional Data. Journal of Statistical Software.

2016

  • Pircalabelu, E., Claeskens, G., & Waldorp, L. J. (2016). Mixed scale joint graphical lasso. Biostatistics, 17(4), 793-806. DOI: 10.1093/biostatistics/kxw025  [details] 
  • Cramer, A. O. J., van Ravenzwaaij, D., Matzke, D., Steingroever, H., Wetzels, R., Grasman, R. P. P. P., ... Wagenmakers, E-J. (2016). Hidden multiplicity in exploratory multiway ANOVA: Prevalence and remedies. Psychonomic Bulletin & Review, 23(2), 640-647. DOI: 10.3758/s13423-015-0913-5  [details] 

2015

  • Costantini, G., Epskamp, S., Borsboom, D., Perugini, M., Mõttus, R., Waldorp, L. J., & Cramer, A. O. J. (2015). State of the aRt personality research: A tutorial on network analysis of personality data in R. Journal of Research in Personality, 54, 13-29. DOI: 10.1016/j.jrp.2014.07.003  [details] 
  • Jahfari, S., Waldorp, L., Ridderinkhof, K. R., & Scholte, H. S. (2015). Visual information shapes the dynamics of corticobasal ganglia pathways during response selection and inhibition. Journal of Cognitive Neuroscience, 27(7), 1344-1359. DOI: 10.1162/jocn_a_00792  [details] 
  • Schmittmann, V. D., Jahfari, S., Borsboom, D., Savi, A. O., & Waldorp, L. J. (2015). Making large-scale networks from fMRI data. PLoS One, 10(9), [e0129074]. DOI: 10.1371/journal.pone.0129074  [details] 
  • Waldorp, L. J., & Schmittmann, V. D. (2015). Computing assortative mixing by degree with the s-metric in networks using linear programming. Journal of applied mathematics, 2015, [580361]. DOI: 10.1155/2015/580361  [details] 
  • van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B. W. J. H., Waldorp, L. J., & Schoevers, R. A. (2015). Association of symptom network structure with the course of depression. JAMA Psychiatry, 72(12), 1219-1226. DOI: 10.1001/jamapsychiatry.2015.2079  [details] 
  • Claeskens, G., Pircalabelu, E., & Waldorp, L. (2015). Constructing graphical models via the focused information criterion. In A. Antoniadis, J-M. Poggi, & X. Brossat (Eds.), Modeling and Stochastic learning for forecasting in high dimensions (pp. 55-78). (Lecture notes in statistics; No. 217). Cham [etc.]: Springer. DOI: 10.1007/978-3-319-18732-7_4  [details] 
  • Pircalabelu, E., Claeskens, G., & Waldorp, L. (2015). A focused information criterion for graphical models. Statistics and Computing, 25(6), 1071-1092. DOI: 10.1007/s11222-014-9504-y  [details] 

2014

  • de Hollander, G., Wagenmakers, E-J., Waldorp, L., & Forstmann, B. (2014). An antidote to the imager's fallacy, or how to identify brain areas that are in limbo. PLoS One, 9(12), e115700. [e115700]. DOI: 10.1371/journal.pone.0115700  [details] 
  • van Borkulo, C. D., Borsboom, D., Epskamp, S., Blanken, T. F., Boschloo, L., Schoevers, R. A., & Waldorp, L. J. (2014). A new method for constructing networks from binary data. Scientific Reports, 4, [5918]. DOI: 10.1038/srep05918  [details] 
  • Guillaume, B., Hua, X., Thompson, P. M., Waldorp, L., & Nichols, T. E. (2014). Fast and accurate modelling of longitudinal and repeated measures neuroimaging data. NeuroImage, 94, 287-302. DOI: 10.1016/j.neuroimage.2014.03.029  [details] 

2013

  • Bringmann, L. F., Scholte, H. S., & Waldorp, L. J. (2013). Matching structural, effective, and functional connectivity: a comparison between structural equation modeling and ancestral graphs. Brain Connectivity, 3(4), 375-385. DOI: 10.1089/brain.2012.0130  [details] 
  • Kievit, R. A., Frankenhuis, W. E., Waldorp, L. J., & Borsboom, D. (2013). Simpson's paradox in psychological science: a practical guide. Frontiers in Psychology, 4, [513]. DOI: 10.3389/fpsyg.2013.00513  [details] 
  • Schmittmann, V. D., Cramer, A. O. J., Waldorp, L. J., Epskamp, S., Kievit, R. A., & Borsboom, D. (2013). Deconstructing the construct: A network perspective on psychological phenomena. New Ideas in Psychology, 31(2), 43-53. DOI: 10.1016/j.newideapsych.2011.02.007  [details] 

2012

  • Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). Qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1-18. [details] 
  • Jahfari, S., Verbruggen, F., Frank, M. J., Waldorp, L. J., Colzato, L., Ridderinkhof, K. R., & Forstmann, B. U. (2012). How preparation changes the need for top-down control of the basal ganglia when inhibiting premature actions. The Journal of Neuroscience, 32(32), 10870-10878. DOI: 10.1523/JNEUROSCI.0902-12.2012  [details] 
  • Kievit, R. A., van Rooijen, H., Wicherts, J. M., Waldorp, L. J., Kan, K-J., Scholte, H. S., & Borsboom, D. (2012). Intelligence and the brain: a model-based approach. Cognitive Neuroscience, 3(2), 89-97. DOI: 10.1080/17588928.2011.628383  [details] 
  • Weeda, W. D., Grasman, R. P. P. P., Waldorp, L. J., van de Laar, M. C., van der Molen, M. W., & Huizenga, H. M. (2012). A fast and reliable method for simultaneous estimation of waveform, amplitude and latency of single-trial EEG/MEG data. PLoS One, 7(6), e38292. DOI: 10.1371/journal.pone.0038292  [details] 

2011

  • Borsboom, D., Cramer, A. O. J., Schmittmann, V. D., Epskamp, S., & Waldorp, L. J. (2011). The small world of psychopathology. PLoS One, 6(11), [e27407]. DOI: 10.1371/journal.pone.0027407  [details] 
  • Christoffels, I. K., Van de Ven, V., Waldorp, L. J., Formisano, E., & Schiller, N. O. (2011). The sensory consequences of speaking: parametric neural cancellation during speech in auditory cortex. PLoS One, 6(5), [e18307]. DOI: 10.1371/journal.pone.0018307  [details] 
  • Jahfari, S., Waldorp, L., van den Wildenberg, W. P. M., Scholte, H. S., Ridderinkhof, K. R., & Forstmann, B. U. (2011). Effective connectivity reveals important roles for both the hyperdirect (fronto-subthalamic) and indirect (fronto-striatal-pallidal) fronto-basal ganglia pathways during response inhibition. The Journal of Neuroscience, 31(18), 6891-6899. DOI: 10.1523/JNEUROSCI.5253-10.2011  [details] 
  • Kievit, R. A., Romeijn, J-W., Waldorp, L. J., Wicherts, J. M., Scholte, H. S., & Borsboom, D. (2011). Mind the gap: a psychometric approach to the reduction problem. Psychological Inquiry, 22(2), 67-87. DOI: 10.1080/1047840X.2011.550181  [details] 
  • Kievit, R. A., Romeijn, J-W., Waldorp, L. J., Wicherts, J. M., Scholte, H. S., & Borsboom, D. (2011). Modeling mind and matter: reductionism and psychological measurement in cognitive neuroscience. Psychological Inquiry, 22(2), 139-157. DOI: 10.1080/1047840X.2011.567962  [details] 
  • Waldorp, L., Christoffels, I., & van de Ven, V. (2011). Effective connectivity of fMRI data using ancestral graph theory: dealing with missing regions. NeuroImage, 54(4), 2695-2705. DOI: 10.1016/j.neuroimage.2010.10.054  [details] 
  • Weeda, W. D., Waldorp, L. J., Grasman, R. P. P. P., van Gaal, S., & Huizenga, H. M. (2011). Functional connectivity analysis of fMRI data using parameterized regions-of-interest. NeuroImage, 54(1), 410-416. DOI: 10.1016/j.neuroimage.2010.07.022  [details] 
  • Weeda, W. D., de Vos, F., Waldorp, L. J., Grasman, R. P. P. P., & Huizenga, H. M. (2011). arf3DS4: an integrated framework for localization and connectivity analysis of fMRI data. Journal of Statistical Software, 44(14). [details] 

2010

  • Cramer, A. O. J., Waldorp, L. J., van der Maas, H. L. J., & Borsboom, D. (2010). Comorbidity: a network perspective. Behavioral and Brain Sciences, 33(2-3), 137-150. DOI: 10.1017/S0140525X09991567  [details] 
  • Cramer, A. O. J., Waldorp, L. J., van der Maas, H. L. J., & Borsboom, D. (2010). Complex realities require complex theories: refining and extending the network approach to mental disorders. Behavioral and Brain Sciences, 33(2-3), 178-193. DOI: 10.1017/S0140525X10000920  [details] 

2009

  • Scholte, H. S., Ghebreab, S., Waldorp, L., Smeulders, A. W. M., & Lamme, V. A. F. (2009). Brain responses strongly correlate with Weibull image statistics when processing natural images. Journal of Vision, 9(4), 29. DOI: 10.1167/9.4.29  [details] 
  • Waldorp, L. (2009). Robust and unbiased variance of GLM coefficients for misspecified autocorrelation and hemodynamic response models in fMRI. International Journal of Biomedical Imaging, 2009(723912), 1-11. DOI: 10.1155/2009/723912  [details] 
  • Weeda, W. D., Waldorp, L. J., Christoffels, I., & Huizenga, H. M. (2009). Activated region fitting: a robust high-power method for fMRI analysis using parameterized regions of activation. Human Brain Mapping, 30(8), 2595-2605. DOI: 10.1002/hbm.20697  [details] 

2017

  • Borsboom, D., Fried, E. I., Epskamp, S., Waldorp, L. J., van Borkulo, C. D., van der Maas, H. L. J., & Cramer, A. O. J. (2017). False alarm? A comprehensive reanalysis of "evidence that psychopathology symptom networks have limited replicability" by Forbes, Wright, Markon, and Krueger (2017). Journal of Abnormal Psychology, 126(7), 989-999. DOI: 10.1037/abn0000306  [details] 

2016

  • Van Borkulo, C., Boschloo, L., Borsboom, D., Penninx, B. W. J. H., Waldorp, L. J., & Schoevers, R. A. (2016). Erratum: Association of symptom network structure with the course of longitudinal depression (JAMA Psychiatry (2015) 72:12 (1219-1226)). JAMA Psychiatry, 73(4), 412. DOI: 10.1001/jamapsychiatry.2016.0024 

2014

  • Claeskens, G., Pircalabelu, E., & Waldorp, L. (2014). Constructing graphical models via the focused information criterion. (KBI; No. 1404). Leuven: University of Leuven. DOI: 10.2139/ssrn.2419382  [details] 

2012

  • Kievit, R. A., Waldorp, L. J., Kan, K. J., & Wicherts, J. M. (2012). Causality: populations, individuals, and assumptions. European Journal of Personality, 26(4), 400-401. DOI: 10.1002/per.1865  [details] 

2008

  • Waldorp, L. (2008). [Review of: A.R. Brazzale, A.C. Davidson (2007) Applied asymptotics: Case studies in small sample statistics]. Biometrics, 64(2), 660-660. [details] 

2014

  • Jahfari, S., Waldorp, L. J., Ridderinkhof, K. R., & Scholte, H. S. (2014). Visual information shapes the dynamics of cortico-basal ganglia pathways during perceptual response selection and inhibition. Journal of Vision, 14(10), [308]. DOI: 10.1167/14.10.308 

2013

  • Jahfari, S., Ridderinkhof, K. R., Waldorp, L., & Scholte, H. S. (2013). The prefrontal cortex and higher sensory areas co-direct the basal ganglia to pass the most optimal response. Psychophysiology, 50(S1), S22. DOI: 10.1111/psyp.12119 
  • van der Leij, A. R., Ridderinkhof, R., Waldorp, L., & Scholte, H. S. (2013). Efficiency of reaction and inhibition are associated with unique white matter network fingerprints in a large (N=950) sample representative of the Dutch population. Abstract from Society for Neuroscience 2013, .
  • Pircalabelu, E., Claeskens, G., & Waldorp, L. J. (2013). Model selection for graphical models using the focused information criterion. Abstract from Workshop of the Scientific Research Network on "Asymptotic Theory for Multidimensional Statistics", .

Journal editor

  • Waldorp, L. J. (editor) (2015). PLoS One (Journal).

Talk / presentation

  • Waldorp, L. J. (invited speaker) (20-11-2013). Invited lecture on Networks in neuroscience, EFPSA, Amsterdam.
  • Waldorp, L. J. (invited speaker) (6-4-2013). Invited lecture on Networks in neuroscience, Christiaan Huygens Seminar, Delft.
  • Waldorp, L. J. (invited speaker) (31-1-2013). Invited keynote on Networks in psychology and neuroscience, EURANDOM, Eindhoven.

2015

  • Haslbeck, J. M. B., & Waldorp, L. J. (2015). Structure estimation for mixed graphical models in high-dimensional data. (arXiv; No. 1510.05677 [stat.AP]). [details] 
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  • No ancillary activities

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