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LongitudinalSilcton

This Jupyter Notebook contains the data analysis pipeline for:
Brucato, M., Nazareth, A., & Newcombe, N. S., (2022) Longitudinal development of cognitive mapping from childhood to adolescence. Journal of Experimental Child Psychology.1

Coding languages: Python, R.

Outline of the Noteboook:

  1. Import raw data from each task
  2. Quality check, code, and format data from each task
  3. Merge data together in one dataframe by participant ID
  4. Calculate descriptive statistics & run outlier detection
  5. Generate manuscript tables
  6. Generate manuscript figures

Manuscript figures generated from this code:

Scatterplots of navigation performance for upper and lower age groups in our sample.

scatter plots of navigation performance

Developmental trend lines of pointing performance by age.

developmental trend lines of pointing performance