| No issue is more critical to the study of crime and delinquency than the
issue of measurement. At the heart of this have been ongoing debates
over the relative advantages and disadvantages of self-report measures
of delinquency. While it is widely accepted that crime rates increase
during adolescence to a peak close to 17 years of age, findings from
self-report measures of multiple cohorts from the National Youth Survey
show declining trends in delinquency regardless of age. Various
researchers have debated the reasons for these discrepant findings,
including period effects, testing effects, and changing content validity
of delinquency measures to name a few. The present paper engages in
these debates and augments previous findings in two ways: 1) by using
multi-level modeling to account for the presence of missing time points
in longitudinal designs, treating these missing data as latent variables
in multivariate outcome models, and 2) by relaxing the classical
assumptions of independent errors and equal variances of these errors.
One of the key benefits of multi-level modeling is that it utilizes all
available longitudinal data even if a respondent misses a time point,
thereby letting researchers assess the effects of sample attrition
across waves of longitudinal data collections.
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Updated 05/20/2006