This article compares the advantages and disadvantages of two multivariate methods for the analysis of small grolup communication data, log-linear contingency table analysis and multivariate analysis of variance, in the context of
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experimental design. The independent conditions were discussion procedure, task solution multiplicity, and discussion topic. Participant communication behaviors, the dependent variables, were coded into a mix of 15 task social, and procedural categories. The analyses of communication indicated that log-linzear
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produced thle most complex models for various behaviors, including both single-factor and multifactor termns. Multivariate analysis of variance (MANOVA) findings at tlte grolup level provided the most parsimonious explanations, with a main effect of discussion procedure. Some MANOVA results at the individual level were similar to loglitnear mnodels in their complexity, whereas others duplicated the results of the group-level MANOVA.
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differing outcomes from these methods point to several design considerations that should be taken account when choosing a statistical test for group communication data.