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Gazepath: An eye-tracking analysis tool that accounts for individual differences and data quality

Eye-trackers are a popular tool for studying cognitive, emotional, and attentional processes in different populations (e.g., clinical and typically developing) and participants of all ages, ranging from infants to the elderly. This broad range of processes and populations implies that there are many inter- and intra-individual differences that need to be taken into account when ...

Infants’ Temperament and Mothers’, and Fathers’ Depression Predict Infants’ Attention to Objects Paired with Emotional Faces

. Acknowledgments The contributions of Evin Aktar, Dorothy J. Mandell, and Maartje E. J. Raijmakers were supported by the University of Amsterdam research priority program ‘Brain and Cognition’. The contributions of

Parameter identification in multinomial processing tree models

Multinomial processing tree models form a popular class of statistical models for categorical data that have applications in various areas of psychological research. As in all statistical models, establishing which parameters are identified is necessary for model inference and selection on the basis of the likelihood function, and for the interpretation of the results. The required ...

Characterizing sequence knowledge using online measures and hidden Markov models

INGMAR VISSER 0 MAARTJE E. J. RAIJMAKERS 0 PETER C. M. MOLENAAR 0 0 University of Amsterdam , Amsterdam, The Netherlands What knowledge do subjects acquire in sequence-learning experiments? How can

Rule transition on the balance scale task: a case study in belief change

Brenda R. J. Jansen Maartje E. J. Raijmakers Ingmar Visser For various domains in proportional reasoning cognitive development is characterized as a progression through a series of increasingly

Inferring the structure of latent class

Present optimization techniques in latent class analysis apply the expectation maximization algorithm or the Newton-Raphson algorithm for optimizing the parameter values of a prespecified model. These techniques can be used to find maximum likelihood estimates of the parameters, given the specified structure of the model, which is defined by the number of classes and, possibly, ...

Finite mixture distribution models of simple discrimination learning

Through the application of finite mixture distribution models, we investigated the existence of distinct modes of behavior in learning a simple discrimination. The data were obtained in a repeated measures study in which subjects aged 6 to 10 years carried out a simple discrimination learning task. In contrast to distribution models of exclusively rational learners or exclusively ...