| Year |
Citation |
Score |
| 2021 |
Wiech K, Eippert F, Vandekerckhove J, Zaman J, Placek K, Tuerlinckx F, Vlaeyen J, Tracey I. Cortico-brainstem mechanisms of biased perceptual decision-making in the context of pain. The Journal of Pain. PMID 34856408 DOI: 10.1016/j.jpain.2021.11.006 |
0.622 |
|
| 2021 |
Loossens T, Dejonckheere E, Tuerlinckx F, Verdonck S. Informing VAR(1) with qualitative dynamical features improves predictive accuracy. Psychological Methods. PMID 34582245 DOI: 10.1037/met0000401 |
0.34 |
|
| 2021 |
Loossens T, Meers K, Vanhasbroeck N, Anarat N, Verdonck S, Tuerlinckx F. Efficient estimation of bounded gradient-drift diffusion models for affect on CPU and GPU. Behavior Research Methods. PMID 34561819 DOI: 10.3758/s13428-021-01674-7 |
0.311 |
|
| 2021 |
Loossens T, Tuerlinckx F, Verdonck S. A comparison of continuous and discrete time modeling of affective processes in terms of predictive accuracy. Scientific Reports. 11: 6218. PMID 33737588 DOI: 10.1038/s41598-021-85320-4 |
0.327 |
|
| 2020 |
Loossens T, Mestdagh M, Dejonckheere E, Kuppens P, Tuerlinckx F, Verdonck S. The Affective Ising Model: A computational account of human affect dynamics. Plos Computational Biology. 16: e1007860. PMID 32413047 DOI: 10.1371/Journal.Pcbi.1007860 |
0.422 |
|
| 2019 |
Lafit G, Tuerlinckx F, Myin-Germeys I, Ceulemans E. A Partial Correlation Screening Approach for Controlling the False Positive Rate in Sparse Gaussian Graphical Models. Scientific Reports. 9: 17759. PMID 31780817 DOI: 10.1038/S41598-019-53795-X |
0.344 |
|
| 2019 |
Mestdagh M, Verdonck S, Meers K, Loossens T, Tuerlinckx F. Prepaid parameter estimation without likelihoods. Plos Computational Biology. 15: e1007181. PMID 31498789 DOI: 10.1371/Journal.Pcbi.1007181 |
0.407 |
|
| 2019 |
van den Bergh D, Tuerlinckx F, Verdonck S. DstarM: an R package for analyzing two-choice reaction time data with the D∗M method. Behavior Research Methods. PMID 31062193 DOI: 10.3758/S13428-019-01249-7 |
0.441 |
|
| 2019 |
Dejonckheere E, Mestdagh M, Houben M, Rutten I, Sels L, Kuppens P, Tuerlinckx F. Complex affect dynamics add limited information to the prediction of psychological well-being. Nature Human Behaviour. PMID 30988484 DOI: 10.1038/S41562-019-0555-0 |
0.335 |
|
| 2019 |
Gvaladze S, De Roover K, Tuerlinckx F, Ceulemans E. Detecting which variables alter component interpretation across multiple groups: A resampling-based method. Behavior Research Methods. PMID 30937846 DOI: 10.3758/S13428-019-01222-4 |
0.317 |
|
| 2018 |
Bulteel K, Tuerlinckx F, Brose A, Ceulemans E. Improved Insight into and Prediction of Network Dynamics by Combining VAR and Dimension Reduction. Multivariate Behavioral Research. 1-23. PMID 30453783 DOI: 10.1080/00273171.2018.1516540 |
0.358 |
|
| 2018 |
Cabrieto J, Adolf J, Tuerlinckx F, Kuppens P, Ceulemans E. Detecting long-lived autodependency changes in a multivariate system via change point detection and regime switching models. Scientific Reports. 8: 15637. PMID 30353143 DOI: 10.1038/S41598-018-33819-8 |
0.366 |
|
| 2018 |
Bulteel K, Mestdagh M, Tuerlinckx F, Ceulemans E. VAR(1) based models do not always outpredict AR(1) models in typical psychological applications. Psychological Methods. PMID 29745683 DOI: 10.1037/Met0000178 |
0.472 |
|
| 2018 |
Mestdagh M, Pe M, Pestman W, Verdonck S, Kuppens P, Tuerlinckx F. Sidelining the mean: The relative variability index as a generic mean-corrected variability measure for bounded variables. Psychological Methods. PMID 29648843 DOI: 10.1037/Met0000153 |
0.334 |
|
| 2018 |
Bringmann LF, Ferrer E, Hamaker EL, Borsboom D, Tuerlinckx F. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model. Multivariate Behavioral Research. 1-22. PMID 29505311 DOI: 10.1080/00273171.2018.1439722 |
0.427 |
|
| 2018 |
Cabrieto J, Tuerlinckx F, Kuppens P, Hunyadi B, Ceulemans E. Testing for the Presence of Correlation Changes in a Multivariate Time Series: A Permutation Based Approach. Scientific Reports. 8: 769. PMID 29335504 DOI: 10.1038/S41598-017-19067-2 |
0.3 |
|
| 2018 |
Voorspoels W, Rutten I, Bartlema A, Tuerlinckx F, Vanpaemel W. Sensitivity to the prototype in children with high-functioning autism spectrum disorder: An example of Bayesian cognitive psychometrics. Psychonomic Bulletin & Review. 25: 271-285. PMID 28290128 DOI: 10.3758/S13423-017-1245-4 |
0.349 |
|
| 2018 |
Cabrieto J, Tuerlinckx F, Kuppens P, Wilhelm FH, Liedlgruber M, Ceulemans E. Capturing correlation changes by applying kernel change point detection on the running correlations Information Sciences. 447: 117-139. DOI: 10.1016/J.Ins.2018.03.010 |
0.31 |
|
| 2017 |
Zaman J, Vanpaemel W, Aelbrecht C, Tuerlinckx F, Vlaeyen JWS. Biased pain reports through vicarious information: A computational approach to investigate the role of uncertainty. Cognition. 169: 54-60. PMID 28825990 DOI: 10.1016/J.Cognition.2017.07.009 |
0.345 |
|
| 2017 |
Steegen S, Tuerlinckx F, Vanpaemel W. Using parameter space partitioning to evaluate a model's qualitative fit. Psychonomic Bulletin & Review. 24: 617-631. PMID 27562764 DOI: 10.3758/S13423-016-1123-5 |
0.436 |
|
| 2017 |
Steegen S, Kim W, Pestman W, Tuerlinckx F, Vanpaemel W. A theoretical note on the prior information criterion Journal of Mathematical Psychology. 80: 33-39. DOI: 10.1016/J.Jmp.2017.06.002 |
0.419 |
|
| 2016 |
Bulteel K, Tuerlinckx F, Brose A, Ceulemans E. Clustering Vector Autoregressive Models: Capturing Qualitative Differences in Within-Person Dynamics. Frontiers in Psychology. 7: 1540. PMID 27774077 DOI: 10.3389/Fpsyg.2016.01540 |
0.416 |
|
| 2016 |
Steegen S, Tuerlinckx F, Gelman A, Vanpaemel W. Increasing Transparency Through a Multiverse Analysis. Perspectives On Psychological Science : a Journal of the Association For Psychological Science. 11: 702-712. PMID 27694465 DOI: 10.1177/1745691616658637 |
0.342 |
|
| 2016 |
Bringmann LF, Hamaker EL, Vigo DE, Aubert A, Borsboom D, Tuerlinckx F. Changing Dynamics: Time-Varying Autoregressive Models Using Generalized Additive Modeling. Psychological Methods. PMID 27668421 DOI: 10.1037/Met0000085 |
0.444 |
|
| 2016 |
Cabrieto J, Tuerlinckx F, Kuppens P, Grassmann M, Ceulemans E. Detecting correlation changes in multivariate time series: A comparison of four non-parametric change point detection methods. Behavior Research Methods. PMID 27383753 DOI: 10.3758/S13428-016-0754-9 |
0.325 |
|
| 2016 |
Kuppens P, Tuerlinckx F, Yik M, Koval P, Coosemans J, Zeng KJ, Russell JA. The relation between valence and arousal in subjective experience varies with personality and culture. Journal of Personality. PMID 27102867 DOI: 10.1111/Jopy.12258 |
0.308 |
|
| 2016 |
Bulteel K, Tuerlinckx F, Brose A, Ceulemans E. Using Raw VAR Regression Coefficients to Build Networks can be Misleading. Multivariate Behavioral Research. 51: 330-44. PMID 27028486 DOI: 10.1080/00273171.2016.1150151 |
0.355 |
|
| 2016 |
Oravecz Z, Tuerlinckx F, Vandekerckhove J. Bayesian Data Analysis with the Bivariate Hierarchical Ornstein-Uhlenbeck Process Model. Multivariate Behavioral Research. 51: 106-19. PMID 26881960 DOI: 10.1080/00273171.2015.1110512 |
0.798 |
|
| 2016 |
Verdonck S, Tuerlinckx F. Factoring out nondecision time in choice reaction time data: Theory and implications. Psychological Review. 123: 208-18. PMID 26641558 DOI: 10.1037/Rev0000019 |
0.447 |
|
| 2016 |
Verdonck S, Meers K, Tuerlinckx F. Efficient simulation of diffusion-based choice RT models on CPU and GPU. Behavior Research Methods. 48: 13-27. PMID 25761391 DOI: 10.3758/S13428-015-0569-0 |
0.371 |
|
| 2015 |
Bringmann L, Ferrer E, Hamaker E, Borsboom D, Tuerlinckx F. Modeling Nonstationary Emotion Dynamics in Dyads Using a Semiparametric Time-Varying Vector Autoregressive Model. Multivariate Behavioral Research. 50: 730-1. PMID 26717135 DOI: 10.1080/00273171.2015.1120182 |
0.409 |
|
| 2015 |
Molenaar D, Tuerlinckx F, van der Maas HL. A Bivariate Generalized Linear Item Response Theory Modeling Framework to the Analysis of Responses and Response Times. Multivariate Behavioral Research. 50: 56-74. PMID 26609743 DOI: 10.1080/00273171.2014.962684 |
0.408 |
|
| 2015 |
Mestdagh M, Verdonck S, Duisters K, Tuerlinckx F. Fingerprint resampling: A generic method for efficient resampling. Scientific Reports. 5: 16970. PMID 26597870 DOI: 10.1038/Srep16970 |
0.304 |
|
| 2015 |
Ebner-Priemer UW, Houben M, Santangelo P, Kleindienst N, Tuerlinckx F, Oravecz Z, Verleysen G, Van Deun K, Bohus M, Kuppens P. Unraveling affective dysregulation in borderline personality disorder: a theoretical model and empirical evidence. Journal of Abnormal Psychology. 124: 186-98. PMID 25603359 DOI: 10.1037/Abn0000021 |
0.714 |
|
| 2015 |
Molenaar D, Tuerlinckx F, van der Maas HL. A generalized linear factor model approach to the hierarchical framework for responses and response times. The British Journal of Mathematical and Statistical Psychology. 68: 197-219. PMID 25109494 DOI: 10.1111/Bmsp.12042 |
0.461 |
|
| 2015 |
van Ravenzwaaij D, Mulder MJ, Tuerlinckx F, Wagenmakers EJ. Paradoxes of optimal decision making: a response to Moran (2014). Psychonomic Bulletin & Review. 22: 307-8. PMID 25002251 DOI: 10.3758/S13423-014-0679-1 |
0.485 |
|
| 2015 |
San Martín E, González J, Tuerlinckx F. On the Unidentifiability of the Fixed-Effects 3PL Model. Psychometrika. 80: 450-67. PMID 24482314 DOI: 10.1007/S11336-014-9404-2 |
0.407 |
|
| 2015 |
Magis D, Tuerlinckx F, De Boeck P. Detection of Differential Item Functioning Using the Lasso Approach Journal of Educational and Behavioral Statistics. 40: 111-135. DOI: 10.3102/1076998614559747 |
0.351 |
|
| 2015 |
Molenaar D, Tuerlinckx F, Maas HLJvd. Fitting diffusion item response theory models for responses and response times using the R package diffIRT Journal of Statistical Software. 66: 1-34. DOI: 10.18637/Jss.V066.I04 |
0.462 |
|
| 2015 |
Hamaker EL, Ceulemans E, Grasman RPPP, Tuerlinckx F. Modeling affect dynamics: State-of-the-art and future challenges Emotion Review. 7: 316-322. DOI: 10.1177/1754073915590619 |
0.474 |
|
| 2014 |
Steegen S, Dewitte L, Tuerlinckx F, Vanpaemel W. Measuring the crowd within again: a pre-registered replication study. Frontiers in Psychology. 5: 786. PMID 25120505 DOI: 10.3389/Fpsyg.2014.00786 |
0.359 |
|
| 2014 |
Wiech K, Vandekerckhove J, Zaman J, Tuerlinckx F, Vlaeyen JW, Tracey I. Influence of prior information on pain involves biased perceptual decision-making. Current Biology : Cb. 24: R679-81. PMID 25093555 DOI: 10.1016/J.Cub.2014.06.022 |
0.667 |
|
| 2014 |
Verdonck S, Tuerlinckx F. The Ising Decision Maker: a binary stochastic network for choice response time. Psychological Review. 121: 422-62. PMID 25090426 DOI: 10.1037/A0037012 |
0.411 |
|
| 2014 |
Bulteel K, Ceulemans E, Thompson RJ, Waugh CE, Gotlib IH, Tuerlinckx F, Kuppens P. DeCon: a tool to detect emotional concordance in multivariate time series data of emotional responding. Biological Psychology. 98: 29-42. PMID 24220647 DOI: 10.1016/J.Biopsycho.2013.10.011 |
0.328 |
|
| 2014 |
González BJ, Boeck PD, Tuerlinckx F. Linear mixed modelling for data from a double mixed factorial design with covariates: a case‐study on semantic categorization response times Journal of the Royal Statistical Society Series C-Applied Statistics. 63: 289-302. DOI: 10.1111/Rssc.12031 |
0.383 |
|
| 2013 |
Braeken J, Kuppens P, De Boeck P, Tuerlinckx F. Contextualized Personality Questionnaires: A Case for Copulas in Structural Equation Models for Categorical Data. Multivariate Behavioral Research. 48: 845-70. PMID 26745596 DOI: 10.1080/00273171.2013.827965 |
0.459 |
|
| 2013 |
Koval P, Ogrinz B, Kuppens P, Van den Bergh O, Tuerlinckx F, Sütterlin S. Affective instability in daily life is predicted by resting heart rate variability. Plos One. 8: e81536. PMID 24312315 DOI: 10.1371/Journal.Pone.0081536 |
0.309 |
|
| 2013 |
Bringmann LF, Vissers N, Wichers M, Geschwind N, Kuppens P, Peeters F, Borsboom D, Tuerlinckx F. A network approach to psychopathology: new insights into clinical longitudinal data. Plos One. 8: e60188. PMID 23593171 DOI: 10.1371/Journal.Pone.0060188 |
0.306 |
|
| 2013 |
Bulteel K, Wilderjans TF, Tuerlinckx F, Ceulemans E. CHull as an alternative to AIC and BIC in the context of mixtures of factor analyzers. Behavior Research Methods. 45: 782-91. PMID 23307573 DOI: 10.3758/S13428-012-0293-Y |
0.393 |
|
| 2013 |
Kuppens P, Tuerlinckx F, Russell JA, Barrett LF. The relation between valence and arousal in subjective experience. Psychological Bulletin. 139: 917-40. PMID 23231533 DOI: 10.1037/A0030811 |
0.404 |
|
| 2013 |
Verduyn P, Tuerlinckx F, Gorp KV. Measuring the duration of emotional experience: the influence of actual duration and response format Quality & Quantity. 47: 2557-2567. DOI: 10.1007/S11135-012-9671-X |
0.31 |
|
| 2013 |
Meulders M, Tuerlinckx F, Vanpaemel W. Constrained Multilevel Latent Class Models for the Analysis of Three-Way Three-Mode Binary Data Journal of Classification. 30: 306-337. DOI: 10.1007/S00357-013-9141-8 |
0.347 |
|
| 2013 |
Verduyn P, Van Mechelen I, Tuerlinckx F, Scherer K. The relation between appraised mismatch and the duration of negative emotions: Evidence for universality European Journal of Personality. 27: 481-494. DOI: 10.1002/Per.1897 |
0.309 |
|
| 2012 |
Kuppens P, Champagne D, Tuerlinckx F. The Dynamic Interplay between Appraisal and Core Affect in Daily Life. Frontiers in Psychology. 3: 380. PMID 23060842 DOI: 10.3389/Fpsyg.2012.00380 |
0.34 |
|
| 2012 |
van Ravenzwaaij D, Mulder MJ, Tuerlinckx F, Wagenmakers EJ. Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test. Frontiers in Psychology. 3: 132. PMID 22615704 DOI: 10.3389/Fpsyg.2012.00132 |
0.561 |
|
| 2011 |
Oravecz Z, Tuerlinckx F, Vandekerckhove J. A hierarchical latent stochastic differential equation model for affective dynamics. Psychological Methods. 16: 468-90. PMID 21823796 DOI: 10.1037/A0024375 |
0.799 |
|
| 2011 |
Lodewyckx T, Tuerlinckx F, Kuppens P, Allen N, Sheeber L. A hierarchical state space approach to affective dynamics. Journal of Mathematical Psychology. 55: 68-83. PMID 21516216 DOI: 10.1016/J.Jmp.2010.08.004 |
0.434 |
|
| 2011 |
Oravecz Z, Tuerlinckx F. The linear mixed model and the hierarchical Ornstein-Uhlenbeck model: some equivalences and differences. The British Journal of Mathematical and Statistical Psychology. 64: 134-60. PMID 21506948 DOI: 10.1348/000711010X498621 |
0.737 |
|
| 2011 |
Vandekerckhove J, Tuerlinckx F, Lee MD. Hierarchical diffusion models for two-choice response times. Psychological Methods. 16: 44-62. PMID 21299302 DOI: 10.1037/A0021765 |
0.725 |
|
| 2011 |
Boeck PD, Bakker M, Zwitser R, Nivard M, Hofman A, Tuerlinckx F, Partchev I. The estimation of item response models with the lmer function from the lme4 package in R Journal of Statistical Software. 39: 1-28. DOI: 10.18637/Jss.V039.I12 |
0.459 |
|
| 2011 |
Lodewyckx T, Kim W, Lee MD, Tuerlinckx F, Kuppens P, Wagenmakers EJ. A tutorial on Bayes factor estimation with the product space method Journal of Mathematical Psychology. 55: 331-347. DOI: 10.1016/J.Jmp.2011.06.001 |
0.59 |
|
| 2010 |
Kuppens P, Oravecz Z, Tuerlinckx F. Feelings change: accounting for individual differences in the temporal dynamics of affect. Journal of Personality and Social Psychology. 99: 1042-60. PMID 20853980 DOI: 10.1037/A0020962 |
0.719 |
|
| 2010 |
Vandekerckhove J, Verheyen S, Tuerlinckx F. A crossed random effects diffusion model for speeded semantic categorization decisions. Acta Psychologica. 133: 269-82. PMID 19962683 DOI: 10.1016/J.Actpsy.2009.10.009 |
0.725 |
|
| 2010 |
Frederickx S, Tuerlinckx F, Boeck PD, Magis D. RIM: A Random Item Mixture Model to Detect Differential Item Functioning Journal of Educational Measurement. 47: 432-457. DOI: 10.1111/J.1745-3984.2010.00122.X |
0.376 |
|
| 2010 |
Wetzels R, Vandekerckhove J, Tuerlinckx F, Wagenmakers EJ. Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task Journal of Mathematical Psychology. 54: 14-27. DOI: 10.1016/J.Jmp.2008.12.001 |
0.738 |
|
| 2009 |
Dutilh G, Vandekerckhove J, Tuerlinckx F, Wagenmakers EJ. A diffusion model decomposition of the practice effect. Psychonomic Bulletin & Review. 16: 1026-36. PMID 19966251 DOI: 10.3758/16.6.1026 |
0.741 |
|
| 2009 |
Braeken J, Tuerlinckx F. Investigating latent constructs with item response models: a MATLAB IRTm toolbox. Behavior Research Methods. 41: 1127-37. PMID 19897820 DOI: 10.3758/Brm.41.4.1127 |
0.454 |
|
| 2009 |
Braeken J, Tuerlinckx F. A mixed model framework for teratology studies. Biostatistics (Oxford, England). 10: 744-55. PMID 19628637 DOI: 10.1093/Biostatistics/Kxp028 |
0.443 |
|
| 2009 |
Martin ES, Gonzalez J, Tuerlinckx F. Identified Parameters, Parameters of Interest and Their Relationships. Measurement: Interdisciplinary Research & Perspective. 7: 97-105. DOI: 10.1080/15366360903117053 |
0.417 |
|
| 2009 |
Verduyn P, Van Mechelen I, Tuerlinckx F, Meers K, Van Coillie H. Intensity profiles of emotional experience over time Cognition & Emotion. 23: 1427-1443. DOI: 10.1080/02699930902949031 |
0.307 |
|
| 2009 |
Oravecz Z, Tuerlinckx F, Vandekerckhove J. A Hierarchical Ornstein–Uhlenbeck Model for Continuous Repeated Measurement Data Psychometrika. 74: 395-418. DOI: 10.1007/S11336-008-9106-8 |
0.799 |
|
| 2008 |
González J, De Boeck P, Tuerlinckx F. A double-structure structural equation model for three-mode data. Psychological Methods. 13: 337-53. PMID 19071998 DOI: 10.1037/A0013269 |
0.301 |
|
| 2008 |
Rouder JN, Tuerlinckx F, Speckman P, Lu J, Gomez P. A hierarchical approach for fitting curves to response time measurements. Psychonomic Bulletin & Review. 15: 1201-8. PMID 19001591 DOI: 10.3758/Pbr.15.6.1201 |
0.431 |
|
| 2008 |
Vandekerckhove J, Tuerlinckx F. Diffusion model analysis with MATLAB: a DMAT primer. Behavior Research Methods. 40: 61-72. PMID 18411528 DOI: 10.3758/Brm.40.1.61 |
0.689 |
|
| 2008 |
Valdivieso L, Schoutens W, Tuerlinckx F. Maximum likelihood estimation in processes of Ornstein-Uhlenbeck type Statistical Inference For Stochastic Processes. 12: 1-19. DOI: 10.1007/S11203-008-9021-8 |
0.309 |
|
| 2007 |
Vandekerckhove J, Tuerlinckx F. Fitting the Ratcliff diffusion model to experimental data. Psychonomic Bulletin & Review. 14: 1011-26. PMID 18229471 DOI: 10.3758/Bf03193087 |
0.718 |
|
| 2007 |
Kuppens P, Tuerlinckx F. Personality traits predicting anger in self-, ambiguous-, and other caused unpleasant situations Personality and Individual Differences. 42: 1105-1115. DOI: 10.1016/J.Paid.2006.09.011 |
0.326 |
|
| 2007 |
Braeken J, Tuerlinckx F, De Boeck P. Copula Functions for Residual Dependency Psychometrika. 72: 393-411. DOI: 10.1007/S11336-007-9005-4 |
0.415 |
|
| 2006 |
Tuerlinckx F, Rijmen F, Verbeke G, De Boeck P. Statistical inference in generalized linear mixed models: a review. The British Journal of Mathematical and Statistical Psychology. 59: 225-55. PMID 17067411 DOI: 10.1348/000711005X79857 |
0.332 |
|
| 2006 |
González J, Tuerlinckx F, De Boeck P, Cools R. Numerical integration in logistic-normal models Computational Statistics and Data Analysis. 51: 1535-1548. DOI: 10.1016/J.Csda.2006.05.003 |
0.345 |
|
| 2005 |
Rijmen F, Tuerlinckx F, Meulders M, Smits DJ, Balázs K. Mixed model estimation methods for the Rasch model. Journal of Applied Measurement. 6: 273-88. PMID 15942071 |
0.326 |
|
| 2005 |
Tuerlinckx F, Boeck PD. Two interpretations of the discrimination parameter Psychometrika. 70: 629-650. DOI: 10.1007/S11336-000-0810-3 |
0.499 |
|
| 2004 |
Tuerlinckx F. The efficient computation of the cumulative distribution and probability density functions in the diffusion model. Behavior Research Methods, Instruments, & Computers : a Journal of the Psychonomic Society, Inc. 36: 702-16. PMID 15641417 DOI: 10.3758/Bf03206552 |
0.329 |
|
| 2004 |
Tuerlinckx F. A multivariate counting process with Weibull-distributed first-arrival times Journal of Mathematical Psychology. 48: 65-79. DOI: 10.1016/J.Jmp.2003.12.001 |
0.411 |
|
| 2003 |
Rijmen F, Tuerlinckx F, De Boeck P, Kuppens P. A nonlinear mixed model framework for item response theory. Psychological Methods. 8: 185-205. PMID 12924814 DOI: 10.1037/1082-989X.8.2.185 |
0.449 |
|
| 2003 |
Verguts T, Storms G, Tuerlinckx F. Decision-bound theory and the influence of familiarity. Psychonomic Bulletin & Review. 10: 141-8. PMID 12747501 DOI: 10.3758/Bf03196478 |
0.328 |
|
| 2002 |
Ratcliff R, Tuerlinckx F. Estimating parameters of the diffusion model: approaches to dealing with contaminant reaction times and parameter variability. Psychonomic Bulletin & Review. 9: 438-81. PMID 12412886 DOI: 10.3758/Bf03196302 |
0.452 |
|
| 2002 |
Tuerlinckx F, De BP, Lens W. Measuring needs with the thematic apperception test: a psychometric study. Journal of Personality and Social Psychology. 82: 448-61. PMID 11902627 DOI: 10.1037/0022-3514.82.3.448 |
0.307 |
|
| 2002 |
Gelman A, Katz JN, Tuerlinckx F. The mathematics and statistics of voting power Statistical Science. 17: 420-435. DOI: 10.1214/Ss/1049993201 |
0.366 |
|
| 2001 |
Tuerlinckx F, Maris E, Ratcliff R, De Boeck P. A comparison of four methods for simulating the diffusion process. Behavior Research Methods, Instruments, & Computers : a Journal of the Psychonomic Society, Inc. 33: 443-56. PMID 11816447 DOI: 10.3758/Bf03195402 |
0.338 |
|
| 2001 |
Tuerlinckx F, Boeck PD. The effect of ignoring item interactions on the estimated discrimination parameters in item response theory. Psychological Methods. 6: 181-195. PMID 11411441 DOI: 10.1037/1082-989X.6.2.181 |
0.363 |
|
| 2000 |
Janssen R, Tuerlinckx F, Meulders M, De Boeck P. A Hierarchical IRT Model for Criterion-Referenced Measurement Journal of Educational and Behavioral Statistics. 25: 285-306. DOI: 10.3102/10769986025003285 |
0.413 |
|
| 2000 |
Gelman A, Goegebeur Y, Tuerlinckx F, Van Mechelen I. Diagnostic checks for discrete data regression models using posterior predictive simulations Journal of the Royal Statistical Society: Series C (Applied Statistics). 49: 247-268. DOI: 10.1111/1467-9876.00190 |
0.45 |
|
| 1999 |
Tuerlinckx F, De Boeck P. Distinguishing Constant and Dimension-Dependent Interaction: A Simulation Study Applied Psychological Measurement. 23: 299-307. DOI: 10.1177/01466219922031419 |
0.366 |
|
| 1998 |
Tuerlinckx F, De Boeck P. Modeling Local Item Dependencies in Item Response Theory Psychologica Belgica. 38: 61. DOI: 10.5334/Pb.925 |
0.316 |
|
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