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Exploring the Reliability of Youth-S...
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Keces, Natasha.
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Exploring the Reliability of Youth-Specific Measures Within Intensive Longitudinal Designs: An Illustration.
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Exploring the Reliability of Youth-Specific Measures Within Intensive Longitudinal Designs: An Illustration./
作者:
Keces, Natasha.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2024,
面頁冊數:
61 p.
附註:
Source: Masters Abstracts International, Volume: 85-08.
Contained By:
Masters Abstracts International85-08.
標題:
Developmental psychology. -
電子資源:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30988875
ISBN:
9798381717679
Exploring the Reliability of Youth-Specific Measures Within Intensive Longitudinal Designs: An Illustration.
Keces, Natasha.
Exploring the Reliability of Youth-Specific Measures Within Intensive Longitudinal Designs: An Illustration.
- Ann Arbor : ProQuest Dissertations & Theses, 2024 - 61 p.
Source: Masters Abstracts International, Volume: 85-08.
Thesis (M.A.)--Tufts University, 2024.
This item must not be sold to any third party vendors.
The computation of a measure's reliability depends on the data set's structure. For intensive longitudinal designs with multiple participants, reliability for both with- and between-person variation across time must be computed. Despite having methods such as multilevel confirmatory factor analyses (MCFA) available to compute multilevel reliability, most multilevel studies do not report reliability at both levels. As such, computing multilevel reliability in an actual data set can illustrate the computational process and demonstrate the comparability of level-specific reliability estimates. This study provides such an illustration. Intensive longitudinal data were collected from 10th grader students (N = 169, Mage = 16.06, 50% female, 93% Black or African American) within their high school in Chicago, Illinois. Students participated in weekly surveys (total observations = 992). Within-person reliabilities (ωw) and between-person reliabilities (ωb) were computed for three-item scales of ethnic-racial affirmation and school belonging. For ethnic-racial affirmation, the respective reliabilities were ωw = 0.655 and ωb = 0.953. For school belonging, the respective results were ωw = 0.739 and ωb = 0.879. This research illustrates how challenges to modeling change and understanding reliability at the two levels of analysis can be successfully addressed with MCFA procedures. I discuss the importance of identifying reliability at both levels in future intensive longitudinal research and the theoretical significance of differences of within- and between-person reliability.
ISBN: 9798381717679Subjects--Topical Terms:
516948
Developmental psychology.
Subjects--Index Terms:
Ethnic-racial affirmation
Exploring the Reliability of Youth-Specific Measures Within Intensive Longitudinal Designs: An Illustration.
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The computation of a measure's reliability depends on the data set's structure. For intensive longitudinal designs with multiple participants, reliability for both with- and between-person variation across time must be computed. Despite having methods such as multilevel confirmatory factor analyses (MCFA) available to compute multilevel reliability, most multilevel studies do not report reliability at both levels. As such, computing multilevel reliability in an actual data set can illustrate the computational process and demonstrate the comparability of level-specific reliability estimates. This study provides such an illustration. Intensive longitudinal data were collected from 10th grader students (N = 169, Mage = 16.06, 50% female, 93% Black or African American) within their high school in Chicago, Illinois. Students participated in weekly surveys (total observations = 992). Within-person reliabilities (ωw) and between-person reliabilities (ωb) were computed for three-item scales of ethnic-racial affirmation and school belonging. For ethnic-racial affirmation, the respective reliabilities were ωw = 0.655 and ωb = 0.953. For school belonging, the respective results were ωw = 0.739 and ωb = 0.879. This research illustrates how challenges to modeling change and understanding reliability at the two levels of analysis can be successfully addressed with MCFA procedures. I discuss the importance of identifying reliability at both levels in future intensive longitudinal research and the theoretical significance of differences of within- and between-person reliability.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30988875
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