Multilevel Measurement of Dimensions of Collaborative Functioning in a Network of Collaboratives that Promote Child and Family Well-Being

Evaluating collaboration between community partners presents a series of methodological challenges (Roussos and Fawcett in
Annu Rev Public Health 21:369–402, 2000; Yin and Kaftarian 1997), one of which is selection of the appropriate level of analysis. When data are collected from multiple
members of multiple settings, multilevel analysis techniques should be used. Multilevel confirmatory factor analysis (MCFA)
is an analytic approach that incorporates the advantages of latent variable measurement modeling and multilevel modeling for
nested data. This study utilizes MCFA on data obtained from an evaluation survey of collaborative functioning provided to
members of 157 community collaboratives in Georgia. This study presents a well-fitting measurement model that includes five
dimensions of collaborative functioning, and a structural component with individual- and collaborative-level covariates. Findings
suggest that members’ role and meeting attendance significantly predicted their assessment of collaboration at the individual
level, and that tenure of collaborative leaders predicted the overall functioning of the collaborative at the collaborative
level. Dimensionality of collaborative functioning and implications of potentially substantial measurement biases associated
with selection of respondents are addressed.