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Data caus repository_B.sav
datasetposted on 17.11.2017 by M.E.J. Raijmakers, T.J.P. van Schijndel, I.Visser
Datasets usually provide raw data for analysis. This raw data often comes in spreadsheet form, but can be any collection of data, on which analysis can be performed.
This study investigated the development of young children’s causal inference by studying variability in behavior. Two possible sources of variability, strategy use and accuracy in strategy execution, were discriminated and related to age. To this end, a relatively wide range of causal inference trials was administered to children of a relatively broad age range: 2- to 5-year-olds. Subsequently, individuals’ response patterns over trials were analyzed with a latent variable technique [e.g. 1]. The results showed that variability in children’s behavior could largely be explained by strategy use: three different strategies were distinguished, and these were found to be related to age. Importantly, this age-related strategy use better explained the variability in children’s behavior than age-related increase in accuracy of executing a single strategy. This study can be considered a first step in introducing a new, fruitful approach for investigating the development of causal inference.
Research priority area
- Brain & Cognition