Psychological Research Methods

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Judging the mood of the crowd: Attention is focused on happy faces [Dataset] Jul 20, 2018 Bucher, Alica;Voss, Andreas, 2018, "Judging the mood of the crowd: Attention is focused on happy faces [Dataset]", https://doi.org/10.11588/data/MES8FE, heiDATA, V1 Previous research on valence biases in face perception revealed inconsistent findings either proposing angry or happy faces to be detected more efficiently. We argue that the typical experimental task in this field, the face-in-the-crowd (FiC) paradigm, lacks ecological validity...
Learning the Likelihood: Using DeepInference for the Estimation of Diffusion-Model and Lévy Flight Parameters [Dataset] Jun 22, 2018 Voss, Andreas;Mertens, Ulf K.;Radev, Stefan T., 2018, "Learning the Likelihood: Using DeepInference for the Estimation of Diffusion-Model and Lévy Flight Parameters [Dataset]", https://doi.org/10.11588/data/HY4OBJ, heiDATA, V1 In the corresponding paper, we use the recently develop DeepInference architecture as a general likelihood-free method to estimate parameters of cognitive models. DeepInference is a machine-learning algorithm based on the training of convolutional neural networks. In a first step...

Judging the mood of the crowd: Attention is focused on happy faces [Dataset]

Jul 20, 2018

Bucher, Alica;Voss, Andreas, 2018, "Judging the mood of the crowd: Attention is focused on happy faces [Dataset]", https://doi.org/10.11588/data/MES8FE, heiDATA, V1

Previous research on valence biases in face perception revealed inconsistent findings either proposing angry or happy faces to be detected more efficiently. We argue that the typical experimental task in this field, the face-in-the-crowd (FiC) paradigm, lacks ecological validity...

Learning the Likelihood: Using DeepInference for the Estimation of Diffusion-Model and Lévy Flight Parameters [Dataset]

Jun 22, 2018

Voss, Andreas;Mertens, Ulf K.;Radev, Stefan T., 2018, "Learning the Likelihood: Using DeepInference for the Estimation of Diffusion-Model and Lévy Flight Parameters [Dataset]", https://doi.org/10.11588/data/HY4OBJ, heiDATA, V1

In the corresponding paper, we use the recently develop DeepInference architecture as a general likelihood-free method to estimate parameters of cognitive models. DeepInference is a machine-learning algorithm based on the training of convolutional neural networks. In a first step...