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A Multilevel Study of Interpersonal Influence in Academic ‘Influence Networks’
Unformatted Document Text:  Influence Networks 26 this tendency, such as a measure of ‘attitudinally-controlled’ individuals (Trafimow & Finlay, 2001), can contribute to explaining the mutual influence of structural and individual variables on influence outcomes. Methodologically, this study illustrates analysis methods that can be used in similar research that involves multilevel predictions between network and individual level variables. An important contribution of this work is that it advances methods used to test propositions that appear in multilevel theories of social influence. Applying multilevel methods to the study of social influence advances both theory and research because it enables tests of cross-level relationships that are inherent in research that focuses on structural impacts on individual level behavior. Multilevel modeling advances social influence theory and research in two very important ways. First, it allows for tests of theoretical formulations already present within the field. Such a test is reported here, where an assumption that appears in the structural theory of social influence and also in diffusion of innovations theory was subjected to empirical scrutiny. Second, multilevel modeling has the potential to advance our theoretical thinking about social influence in that it enables investigation of many other individual and structural variables related to the influence process. Many teaching behaviors were used to represent a range of attitudes at the individual level, and these behaviors were represented by the random-effect variable used within the multilevel model. The random-effects multilevel model employed in this research exemplifies a way to model multiple domains to discover those behaviors that are related to the centrality- influence link. This need is recognized by Friedkin, who suggests, “the magnitude of the effects of structural bases of power on interpersonal influence probably depends on the issue” (1993, p.

Authors: Wolski, Stacy.
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Influence Networks 26
this tendency, such as a measure of ‘attitudinally-controlled’ individuals (Trafimow & Finlay,
2001), can contribute to explaining the mutual influence of structural and individual variables on
influence outcomes.
Methodologically, this study illustrates analysis methods that can be used in similar
research that involves multilevel predictions between network and individual level variables.
An important contribution of this work is that it advances methods used to test propositions that
appear in multilevel theories of social influence. Applying multilevel methods to the study of
social influence advances both theory and research because it enables tests of cross-level
relationships that are inherent in research that focuses on structural impacts on individual level
behavior.
Multilevel modeling advances social influence theory and research in two very important
ways. First, it allows for tests of theoretical formulations already present within the field. Such
a test is reported here, where an assumption that appears in the structural theory of social
influence and also in diffusion of innovations theory was subjected to empirical scrutiny.
Second, multilevel modeling has the potential to advance our theoretical thinking about social
influence in that it enables investigation of many other individual and structural variables related
to the influence process.
Many teaching behaviors were used to represent a range of attitudes at the individual
level, and these behaviors were represented by the random-effect variable used within the
multilevel model. The random-effects multilevel model employed in this research exemplifies a
way to model multiple domains to discover those behaviors that are related to the centrality-
influence link. This need is recognized by Friedkin, who suggests, “the magnitude of the effects
of structural bases of power on interpersonal influence probably depends on the issue” (1993, p.


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