The goal of the current study was to develop a two level, hierarchical typology of child school behavior (ages 6–11) using the norming data for the revised Behavioral Assessment System for Children Teacher Rating - Child form (BASC-2 TRS-C Reynolds & Kamphaus, 2004). To obtain the two tiers of this classification system, two multivariate classification procedures were employed: latent class cluster analysis (LCCA) and cluster analysis (CA). The first tier of the resulting classification system consited of latent classess, whereas the second tier was represented by the clusters identified within each latent class. Distinct clusters and latent classes of child school behavior were hypothesized to underlie the data based on the findings of previous research with the original and the revised BASC TRS-C norming data (DiStefano & Kamphaus, 2006; DiStefano, Kamphaus & Mîndrilă, 2010).
CA and LCCA were first conducted with the entire data set. The individuals' group memberships in the two classification systems were compared to determine whether the two classification procedures provided convergent results, and to illustrate the distribution of clusters across latent classes. To obtain a hierarchical classification system by identifying the clusters subordinated to each latent class, the BASC-2 TRS-C sample was divided into subsamples based on individuals' latent class membership, and CA was conducted separately with each subsample. Individuals' cluster memberships within the entire sample and within latent classes were compared to determine the proportion of students located in analogous clusters and the proportion of students whose cluster membership changed. The resulting hierarchical typology includes three latent classes that describe three different levels of adaptation to the school environment: (a) Adequate Adjustment (AA), (b) Mild Adjustment Difficulties (MAD), and (c) Functionally Impaired Adjustment (FIA). The clusters identified within each latent class represent the second tier of the classification system. The AA latent class included the (a) Well-Adapted, (b) Average, and (c) Worry clusters. The clusters identified within the MAD latent class were: (a) Academic Problems, (b) Physical Complaints, (c) Disruptive Behavior Problems, and (d) Internalizing Problems. Finally, the FIA latent class comprised the (a) Clinical Problems - External and (b) Clinical Problems - Internal clusters. This hierarchical typology identifies the behavioral profiles that are most frequently encountered in the population of U.S. children, and includes a wide spectrum of behavioral types (both adaptive and maladaptive). Each behavioral profile is defined in terms of its most prominent characteristics and degree of adaptability to the school environment. Furthermore, the proposed classification system facilitates the identification of students who have difficulties adjusting to the school environment and may need targeted intervention.
|Advisor:||Gredler, Margaret, DiStefano, Christine A.|
|Commitee:||Edens, Kellah, Greer, Fred|
|School:||University of South Carolina|
|Department:||Educational Psychology / Research|
|School Location:||United States -- South Carolina|
|Source:||DAI-A 73/09(E), Dissertation Abstracts International|
|Keywords:||Child behavioral and emotional problems, Classification, Cluster analysis, Latent class cluster analysis, School adjustment, Typology|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be