Literature DB >> 21528103

Multilevel Confirmatory Factor Analysis of a Scale Measuring Interagency Collaboration of Children's Mental Health Agencies.

Robert F Dedrick, Paul E Greenbaum.   

Abstract

Multilevel confirmatory factor analysis was used to evaluate the factor structure underlying the 12-item, three-factor Interagency Collaboration Activities Scale (IACS) at the informant level and at the agency level. Results from 378 professionals (104 administrators, 201 service providers, and 73 case managers) from 32 children's mental health service agencies supported a correlated three-factor model at each level and indicated that the item loadings were not significantly (p < .05) different across levels. Reliability estimates of the three factors (Financial and Physical Resource Activities, Program Development and Evaluation Activities, and Collaborative Policy Activities) at the agency level were .81, .60, and .72, respectively, while these estimates were .79, .82, and .85 at the individual level. These multilevel results provide support for the construct validity of the scores from the IACS. When the IACS was examined in relation to level-1 and level-2 covariates, results showed that participants' characteristics (i.e., age, job role, gender, educational level, and number of months employed) and agency characteristics (i.e., state location and number of employees) were not significantly (p > .05) related to levels of interagency collaboration.

Entities:  

Year:  2011        PMID: 21528103      PMCID: PMC3082154          DOI: 10.1177/1063426610365879

Source DB:  PubMed          Journal:  J Emot Behav Disord        ISSN: 1063-4266


  9 in total

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Authors:  Stacey R Friedman; Jesse Reynolds; Michael A Quan; Stephanie Call; Cindy A Crusto; Joy S Kaufman
Journal:  Eval Program Plann       Date:  2007-04-19
  9 in total
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7.  Prevention Service System Transformation Using Communities That Care.

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9.  Modeling contextual effects using individual-level data and without aggregation: an illustration of multilevel factor analysis (MLFA) with collective efficacy.

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