Identifying Student Subgroups as a Function of School Level Attributes: A Multilevel Latent Class Analysis.

ABSTRACT: The purpose of the present study was to profile high school students' achievement as a function of their demographic characteristics, parent attributes (e.g., education), and school behaviors (e.g., number of absences). Students were nested within schools in the Saudi Arabia Kingdom. Out of a large sample of 500k, participants involved 3 random samples of 2,000 students measured during the years 2016, 2017, and 2018. Randomization was conducted at the student level to ensure that all school units will be represented and at their respective frequency. Students were nested within 50 high schools. We adopted the multilevel latent profile analysis protocol put forth by Schmiege et al. (2018) and Mäkikangas et al. (2018) that account for nested data and tested latent class structure invariance

SUBMITTER: Sideridis GD 

PROVIDER: S-EPMC7952435 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature