Description

This data set is from a simple discrimation learning experiment. It consists of 192 binary series of responses of different lengths. This is a subset of the data described by Raijmakers et al. (2001), and it is analyzed much more extensively using latent Markov models and depmix in Schmittmann et al. (2006) and Visser et al. (2006)..

Usage

Format

A data frame with a total of 3139 observations on the following variable:

acc

a factor of accuracy scores (incorrect/correct)

Source

Maartje E. J. Raijmakers, Conor V. Dolan and Peter C. M. Molenaar (2001). Finite mixture distribution models of simple discrimination learning. Memory \& Cognition, vol 29(5).

Ingmar Visser, Verena D. Schmittmann, and Maartje E. J. Raijmakers (2007). Markov process models for discrimination learning. In: Kees van Montfort, Han Oud, and Albert Satorra (Eds.), Longitudinal models in the behavioral and related sciences, Mahwah (NJ): Lawrence Erlbaum Associates.

Verena D. Schmittmann, Ingmar Visser and Maartje E. J. Raijmakers (2006). Multiple learning modes in the development of rule-based category-learning task performance. Neuropsychologia, vol 44(11), p. 2079-2091.