Longitudinal Dynamic Analyses of Depression and Academic Achievement in the Hawaiian High Schools Health Survey using Contemporary Latent Variable Change Models
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields

Dates

to

Document Data
Library
People
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page

CDC STACKS serves as an archival repository of CDC-published products including scientific findings, journal articles, guidelines, recommendations, or other public health information authored or co-authored by CDC or funded partners. As a repository, CDC STACKS retains documents in their original published format to ensure public access to scientific information.
i

Longitudinal Dynamic Analyses of Depression and Academic Achievement in the Hawaiian High Schools Health Survey using Contemporary Latent Variable Change Models

Filetype[PDF-3.55 MB]


English
Details Supporting Files You May Also Like

Details:

  • Alternative Title:
    Struct Equ Modeling
  • Personal Author:
  • Description:
    The scientific literature consistently supports a negative relationship between adolescent depression and educational achievement, but we are certainly less sure on the causal determinants for this robust association. In this paper we present multivariate data from a longitudinal cohort-sequential study of high school students in Hawai'i (following McArdle, 2009; McArdle, Johnson, Hishinuma, Miyamoto, & Andrade, 2001). We first describe the full set of data on academic achievements and self-reported depression. We then carry out and present a progression of analyses in an effort to determine the accuracy, size, and direction of the dynamic relationships among depression and academic achievement, including gender and ethnic group differences. We | three recently available forms of longitudinal data analysis: (1) | -- We apply these methods to cohort-sequential data with relatively large blocks of data which are incomplete for a variety of reasons (Little & Rubin, 1987; McArdle & Hamagami, 1992). (2) | (Muthén & Muthén, 2006) -- We use a variety of statistical and psychometric measurement models, including ordinal measurement models to help clarify the strongest patterns of influence. (3) | (DSEMs; McArdle, 2009). We found the DSEM approach taken here was viable for a large amount of data, the assumption of an invariant metric over time was reasonable for ordinal estimates, and there were very few group differences in dynamic systems. We conclude that our dynamic evidence suggests that depression affects academic achievement, and not the other way around. We further discuss the methodological implications of the study.
  • Source:
    Struct Equ Modeling. 21(4):608-629
  • Pubmed ID:
    25598650
  • Pubmed Central ID:
    PMC4293544
  • Document Type:
    Journal Article
  • Funding:
  • Volume:
    21
  • Issue:
    4
  • Collection(s):
  • Main Document Checksum:
  • Download URL:
  • File Type:

You May Also Like

Checkout today's featured content at stacks.cdc.gov