title: Assessing categorization performance at the individual level: a comparison of Monte Carlo simulation and probability estimate model procedures.
abstract: Two analytical procedures for identifying young children as categorizers, the Monte Carlo Simulation and the Probability Estimate Model, were compared. Using a sequential touching method, children aged 12, 18, 24, and 30 months were given seven object sets representing different levels of categorical classification. From their touching performance, the probability that children were categorizing was then determined independently using Monte Carlo Simulation and the Probability Estimate Model. The two analytical procedures resulted in different percentages of children being classified as categorizers. Results using the Monte Carlo Simulation were more consistent with group-level analyses than results using the Probability Estimate Model. These findings recommend using the Monte Carlo Simulation for determining individual categorizer classification.
authors.affiliation: Department of Psychology, Colby College, 5553 Mayflower Hill, Waterville, ME 04901, USA. Martha.Arterberry@colby.edu
authors.forename: Martha E
authors.initials: ME
authors.lastname: Arterberry
authors.forename: Marc H
authors.initials: MH
authors.lastname: Bornstein
authors.forename: O Maurice
authors.initials: OM
authors.lastname: Haynes
mesh_terms: D002675:Child, Preschool; D002965:Classification / Q000379:methods; D005260:Female; D006801:Humans; D007206:Individuality; D007223:Infant; D008297:Male; D008960:Models, Psychological; D009010:Monte Carlo Method; D010775:Photic Stimulation / Q000379:methods; D011337:Probability Learning; D011597:Psychomotor Performance / Q000502:physiology; D011897:Random Allocation