Ethnic background, therapeutic alliance, and treatment retention in functional family therapy with adolescents who abuse substances.

In this study, the authors examined the role of balance between adolescent-therapist and parent-therapist alliances in the retention of functional family therapy clients. Therapeutic alliances of mothers, fathers, and adolescents were assessed from videotapes of the 1st treatment session for 43 Hispanic and 43 Anglo families. Hispanic families who dropped out before completing the requisite number of sessions were found to have greater imbalance in alliance (parent-adolescent) than those who did complete therapy. However, this finding was not replicated with Anglo families. Results are interpreted in terms of previous research on family-level balanced alliance effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mixed-effects logistic regression for estimating transitional probabilities in sequentially coded observational data.

This article demonstrates the use of mixed-effects logistic regression (MLR) for conducting sequential analyses of binary observational data. MLR is a special case of the mixed-effects logit modeling framework, which may be applied to multicategorical observational data. The MLR approach is motivated in part by G. A. Dagne, G. W. Howe, C. H. Brown, & B. O. Muthén (2002) advances in general linear mixed models for sequential analyses of observational data in the form of contingency table frequency counts. The advantage of the MLR approach is that it circumvents obstacles in the estimation of random sampling error encountered using Dagne and colleagues' approach. This article demonstrates the MLR model in an analysis of observed sequences of communication in a sample of young adult same-sex peer dyads. The results obtained using MLR are compared with those of a parallel analysis using Dagne and colleagues' linear mixed model for binary observational data in the form of log odds ratios. Similarities and differences between the results of the 2 approaches are discussed. Implications for the use of linear mixed models versus mixed-effects logit models for sequential analyses are considered. (PsycINFO Database Record (c) 2010 APA, all rights reserved)