Application of multilevel IRT modeling to the study of self-esteem in adolescents
Abstract
The relationships between predictor variables and item response theory
(IRT) latent trait estimates has traditionally been explored using a two-step
approach of first, estimating IRT parameters and second, using the resulting latent
trait estimates as dependent variables in a regression analysis. Recently, it has
been shown that multilevel IRT modeling can be used to estimate the relationship
between latent traits and predictor variables more accurately than the two-step
approach (Adams, Wilson, & Wu, 1997). Kamata’s (1999; 2001) three-level IRT
model expands the traditional two-level IRT model to situations in which person
are nested within some setting, such as a classroom or school. Formulation of the
model in this manner allows for the study of complex relationships between latent
trait estimates and predictor variables in a multilevel context. While in the past
ten years there has been a large increase in the use of multilevel models in
psychological and educational research, multilevel IRT models have rarely been
utilized in applied research.
The lack of applied research with multilevel IRT modeling motivated the
use of Kamata’s multilevel IRT model (1999; 2001) to study self-esteem in
adolescents. The present study used data collected during the norming of the
CFSEI-3 (Battle, 2002) from 905 adolescents in 13 different sites. Specifically,
this study examined the relationships between academic self-esteem, demographic
characteristics of the adolescent and characteristics that describe the social context
of the adolescent. The same relationships were examined using general selfesteem.
The results support gender and age differences in academic self-esteem
and a gender by age interaction in general self-esteem. The variation in the nature
of such relationships across the 13 sites encourages the use of multilevel modeling
in the study of adolescent self-esteem. As well, the differences in the
relationships of demographic variables with academic and general self-esteem
encourages the study of both the global and specific facets of self-esteem.
Estimation problems were encountered with the more complex models and those
models studying ethnic differences in self-esteem. The causes of such estimation
problems are discussed. As well, the advantages and potential problems in using
multilevel IRT models in applied research are discussed.
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