Statistical treatment of looking-time data

Gergely Csibra, Mikolaj Hernik, Olivier Mascaro, Denis Tatone, Máté Lengyel

Research output: Article

47 Citations (Scopus)

Abstract

Looking times (LTs) are frequently measured in empirical research on infant cognition. We analyzed the statistical distribution of LTs across participants to develop recommendations for their treatment in infancy research. Our analyses focused on a common within-subject experimental design, in which longer looking to novel or unexpected stimuli is predicted. We analyzed data from 2 sources: an in-house set of LTs that included data from individual participants (47 experiments, 1,584 observations), and a representative set of published articles reporting group-level LT statistics (149 experiments from 33 articles). We established that LTs are log-normally distributed across participants, and therefore, should always be log-transformed before parametric statistical analyses. We estimated the typical size of significant effects in LT studies, which allowed us to make recommendations about setting sample sizes. We show how our estimate of the distribution of effect sizes of LT studies can be used to design experiments to be analyzed by Bayesian statistics, where the experimenter is required to determine in advance the predicted effect size rather than the sample size. We demonstrate the robustness of this method in both sets of LT experiments.

Original languageEnglish
Pages (from-to)521-536
Number of pages16
JournalDevelopmental psychology
Volume52
Issue number4
DOIs
Publication statusPublished - ápr. 1 2016

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ASJC Scopus subject areas

  • Demography
  • Developmental and Educational Psychology
  • Life-span and Life-course Studies

Cite this

Csibra, G., Hernik, M., Mascaro, O., Tatone, D., & Lengyel, M. (2016). Statistical treatment of looking-time data. Developmental psychology, 52(4), 521-536. https://doi.org/10.1037/dev0000083