%0 Journal Article
%T Multilevel Modeling With Stat
%A Hsien-Yuan Hsu
%A Minjung Kim
%J Journal of Educational and Behavioral Statistics
%@ 1935-1054
%D 2019
%R 10.3102/1076998618811383
%X Given the natural hierarchical structure in school-setting data, multilevel modeling (MLM) has been widely employed in education research using a number of different statistical software packages. The purpose of this article is to review a recent feature of Stat-JR, the statistical analysis assistants (SAAs) embedded in Stat-JR (Version 1.0.5), with regard to their use for MLM. In this article, we review the features of Stat-JR¡¯s SAAs and illustrate how to implement SAAs, using one of the Stat-JR interfaces to analyze multilevel models for the 1982 High School and Beyond data set. Results from Stat-JR SAA are compared with the results using HLM7.01 software. We also discuss recommendations and implications for future users of SAAs
%K achievement
%K assessment
%K hierarchical linear modeling
%K student knowledge
%U https://journals.sagepub.com/doi/full/10.3102/1076998618811383