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I have data where I am examining the moderating effect of a group-level variable (performance) on the relationship between two individual-level variables, X (2 experimental conditions) and Y (attitude change score calculated from a within-person repeated measure); i.e., my research question is: Does group performance moderate the effect an experimental manipulation has on group leaders' attitude change? (Attitude change = attitude at time 2 - attitude at time 1)

Thus, the sample I'm examining at the individual level are group leaders (one leader per group), so they should not share variance with one another on the group-level variable (an objective group performance measure) and I'm not including any other group members in the analysis. Am I able to conduct a simple moderation analysis (as though I had all individual-level variables), or is there a multilevel approach more appropriate for this situation?

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From what you describe, without any information on the individual members of the group except the leader, it's not clear what a "multilevel" model would be. Your outcomes are for the group leaders, the experimental conditions are specific to group leaders (even if the conditions might have been applied to the entire group), and the group-performance measures are specific to group leaders.

Unless there's something missing from the description, I don't see how you could do anything other than an analysis at the level of group leaders.

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