Application of Multilevel Latent Class Analysis to Identify Achievement and Socio-Economic Typologies in the 20 Wealthiest Countries

  •  W. Finch    
  •  Gregory Marchant    


There has been increased interest in cross-national comparisons of educational achievement, particularly using the data provided through the Programme for International Student Assessment (PISA). The growing tendency in the popular media is to characterize such comparisons by ranking nations based upon mean achievement test scores. However, recent work has demonstrated that the way in which students are organized in schools has a impact on student achievement. The current study demonstrated the utility of a relatively new statistical technique, the nonparametric latent class model, to investigate the cross national organization of schools and its relationship to student achievement and socio-economic status. The results demonstrated that indeed, it is not enough to simply compare mean achievement performance across countries, but rather that the ways in which nations organize students into schools is also associated with test performance. The results of this study highlight both the importance of understanding school organizational context, and the analytic power of the nonparametric latent class model.

This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1927-0526
  • ISSN(Online): 1927-0534
  • Started: 2011
  • Frequency: semiannual

Journal Metrics

(The data was calculated based on Google Scholar Citations)

1. Google-based Impact Factor (2021): 1.11
2. h-index (December 2021): 29
3. i10-index (December 2021): 87
4. h5-index (December 2021): N/A
5. h5-median (December 2021): N/A