dr. I. (Ingmar) Visser

List

Faculty of Social and Behavioural Sciences
Programme group Developmental Psychology
Weesperplein 4
1018 XA Amsterdam
I.Visser@uva.nl
T: 0205256723
T: 0205256830

Profile
Publications
Ancillary activities

For more information see my homepage:

http://www.ingmar.org/

key publications(4)
refereed(23)
academic(8)
professional(1)
supervised theses(1)
doctoral thesis(1)

2011

I. Visser (2011). Seven things to remember about hidden Markov models: a tutorial on Markovian models for time series. Journal of Mathematical Psychology, 55 (6), 403-415. doi: 10.1016/j.jmp.2011.08.002

2010

I. Visser, B.R.J. Jansen & M. Speekenbrink (2010). A framework for discrete change. In P.C.M. Molenaar & K.M. Newell (Eds.), Individual pathways of change: statistical models for analyzing learning and development (pp. 109-123). Washington: APA Science.
I. Visser & M. Speekenbrink (2010). depmixS4: an R-package for hidden Markov models. Journal of Statistical Software, 36 (7), 1-21.[go to publisher's site]

2007

I. Visser, M.E.J. Raijmakers & P.C.M. Molenaar (2007). Characterizing sequence knowledge using online measures and hidden Markov models. Memory & Cognition, 35, 1502-1517.

2014

B.M.C.W. van Bers, I. Visser & M. Raijmakers (2014). Preschoolers learn to switch with causally related feedback. Journal of Experimental Child Psychology, 126, 91-102. doi: 10.1016/j.jecp.2014.03.007
I. Visser & M. Speekenbrink (2014). Comments on: Latent Markov models: a review of a general framework for the analysis longitudinal data with covariates. Test, 23 (3), 478-483. doi: 10.1007/s11749-014-0389-z
M.E.J. Raijmakers, V.D. Schmittmann & I. Visser (2014). Costs and benefits of automatization in category learning of ill-defined rules. Cognitive Psychology, 69, 1-24. doi: 10.1016/j.cogpsych.2013.12.002
I. Visser & M. Speekenbrink (2014). It's a Catastrophe! Testing dynamics between competing cognitive states using mixture and hidden Markov models. In COGSCI 2014: cognitive science meets artificial intelligence: human and artifical agents in interactive contexts (pp. 1688-1693). Austin, TX: Cognitive Science Society.[go to publisher's site]
B.M.C.W. van Bers, I. Visser & M. Raijmakers (2014). Preschoolers can form abstract rule representations regardless of cognitive flexibility. Journal of Experimental Child Psychology, 124, 50-66. doi: 10.1016/j.jecp.2014.01.017
L.M. Andersen, I. Visser, E.A. Crone, P.C.M.P. Koolschijn & M.E.J. Raijmakers (2014). Cognitive strategy use as an index of developmental differences in neural responses to feedback. Developmental Psychology, 50 (12), 2686-2696. doi: 10.1037/a0038106

2012

I. Visser & M.E.J. Raijmakers (2012). Developing representations of compound stimuli. Frontiers in Psychology, 3, 73. doi: 10.3389/fpsyg.2012.00073[go to publisher's site]

2011

B.M.C.W. van Bers, I. Visser, T.J.P. van Schijndel, D.J. Mandell & M.E.J. Raijmakers (2011). The dynamics of development on the Dimensional Change Card Sorting task. Developmental Science, 14 (5), 960-971. doi: 10.1111/j.1467-7687.2011.01045.x
G. Dutilh, E.-J. Wagenmakers, I. Visser & H.L.J. van der Maas (2011). A phase transition model for the speed-accuracy trade-off in response time experiments. Cognitive Science, 35 (2), 211-250. doi: 10.1111/j.1551-6709.2010.01147.x
I. Visser (2011). Seven things to remember about hidden Markov models: a tutorial on Markovian models for time series. Journal of Mathematical Psychology, 55 (6), 403-415. doi: 10.1016/j.jmp.2011.08.002
H.M. Huizenga, I. Visser & C.V. Dolan (2011). Testing overall and moderator effects meta-regression. The British Journal of Mathematical & Statistical Psychology, 64 (1), 1-19. doi: 10.1348/000711010X522687

2010

I. Visser, B.R.J. Jansen & M. Speekenbrink (2010). A framework for discrete change. In P.C.M. Molenaar & K.M. Newell (Eds.), Individual pathways of change: statistical models for analyzing learning and development (pp. 109-123). Washington: APA Science.
I. Visser (2010). [Review of the book Hidden Markov models for time series: an introduction using R.]. Journal of Mathematical Psychology, 54(6), 509-511.
T. Pronk & I. Visser (2010). The role of reversal frequency in learning noisy second order conditional sequences. Consciousness and Cognition, 19 (2), 627-635. doi: 10.1016/j.concog.2009.12.008
I. Visser & M. Speekenbrink (2010). depmixS4: an R-package for hidden Markov models. Journal of Statistical Software, 36 (7), 1-21.[go to publisher's site]
A.C.K. van Duijvenvoorde, B.R.J. Jansen, I. Visser & H.M. Huizenga (2010). Affective and cognitive decision making in adolescents. Developmental Neuropsychology, 35 (5), 539-554. doi: 10.1080/875656412010494749

2009

I. Visser, M.E.J. Raijmakers & E.M. Pothos (2009). Individual strategies in artificial grammar learning. The American Journal of Psychology, 122 (3), 293-307.

2008

D. Borsboom & I. Visser (2008). Semantic cognition or data mining? Behavioral and Brain Sciences, 31 (6), 714-715.

2007

I. Visser, M.E.J. Raijmakers & P.C.M. Molenaar (2007). Characterizing sequence knowledge using online measures and hidden Markov models. Memory & Cognition, 35, 1502-1517.
B.R.J. Jansen, M.E.J. Raijmakers & I. Visser (2007). Rule transition on the balance scale task: A case study in belief change. Synthese, 155, 211-236.

2006

I. Visser & T. Blaazer (2006). Estimating correlations and reliabilities of implicit and explicit tests using a latent variable approach. In R. Sun (Ed.), Proceedings of the 28th Annual Conference of the Cognitive Science Society (pp. 2317-2322). Mahwah (NJ): Lawrence Erlbaum Associates.
V. Schmittmann, I. Visser & M.E.J. Raijmakers (2006). Multiple learning modes in the development of performance on a rule-based category-learning task. Neuropsychologia, 44, 2079-2091.

2005

H.L.J. van der Maas, M.E.J. Raijmakers & I. Visser (2005). Inferring the structure of latent class models using a genetic algorithm. Behavior Research Methods, 37, 340-352.

2011

I. Visser (2011). Methodological solipsism. In P.C. Hogan (Ed.), The Cambridge encyclopedia of language sciences (pp. 497). Cambridge: Cambridge University Press.

2009

I. Visser, M.E.J. Raijmakers & H.L.J. van der Maas (2009). Hidden Markov models for individual time series. 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. 269-289). New York: Springer.

2007

I. Visser, V. Schmittmann & M.E.J. Raijmakers (2007). Markov process models for discrimination learning. In K. van Montford, J. Oud & A. Satorra (Eds.), Longitudinal models in the behavioral and related sciences (pp. 337-365). Mahwah (NJ): Lawrence Erlbaum Associates.

2005

H.L.J. van der Maas, M.E.J. Raijmakers & I. Visser (2005). Inferring the structure of latent class models using a genetic algorhithm. Behavior Research Methods, 37 (2), 340-352.
V. Schmittmann, M.E.J. Raijmakers & I. Visser (2005). Multiple Learning Modes in the Development of Rule-Based Category-learning Task Performance. In B. Hommel, G.P.H. Band, W. La Heij & G. Wolters (Eds.), Fourteenth Conference of the European Society for Cognitive Psychology: Proceedings. The Netherlands: Leiden University.

2000

I. Visser, M.E.J. Raijmakers & P.C.M. Molenaar (2000). Reaction times and predictions in sequence learning: A comparison. In Twenty-second annual conference of the Cognitive Science Society.
P.C.M. Molenaar, I. Visser & M.E.J. Raijmakers (2000). Confidence intervals for hidden Markov model parameters. The British Journal of Mathematical & Statistical Psychology, 53 (2), 317-327.

1998

I. Visser, M.E.J. Raijmakers & P.C.M. Molenaar (1998). Statistical properties of hidden Markov models. In . Leuven: International Workshop on Advanced Black-Box Techniques for Nonlinear Modeling.

2008

I. Visser (2008). Book review (Rissanen) [Review of the book Information and complexity in statistical modeling]. Kwantitatieve Methoden, 1-2.

2014

B.M.C.W. van Bers (2014, March 20). Dynamics, models, and mechanisms of the cognitive flexibility of preschoolers. Universiteit van Amsterdam (203 pag.). Supervisor(s): prof.dr. M.E.J. Raijmakers & dr. I. Visser.

2002

I. Visser (2002, May 16). Rules and associations : hidden Markov models and neural networks in the psychology of learning. Universiteit van Amsterdam (138 pag.). Supervisor(s): prof.dr. P.C.M. Molenaar & prof.dr. M.E.J. Raijmakers.

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