Comparing correlations based on individual-level and aggregated data.

Researchers are often interested in comparing correlations between variables at different levels of analysis (e.g., individual and organizational) to determine if the same relationship holds across the levels. A special situation emerges when correlations at higher levels are based on aggregated data. This article contains an analysis of the nature of the relationship between correlations based on individual-level data and correlations based on aggregated data from individuals. In particular, the conditions under which differences between individual correlations and correlations based on aggregates represent statistical artifacts or meaningful differences are explored. In recent years, levels-of-analysis issues and understanding relationships between levels (e.g., individual, group, and organizational) have become important themes in organizational research (e.g., Dansereau, Alluto, Dansereau Glick, 1985; Click James, 1982; Mossholder Roberts, Hulin, & Rousseau, 1978). As a result, some researchers have begun to hypothesize that stronger relationships between variables may be found at higher levels of analysis. For example, Schneider (1985) suggested that research is needed to assess relationships at the group or organizational level in many areas that have traditionally been studied at the individual level, such as motivation and leadership, leadership and organizational performance, and absenteeism and attitudes. Comparisons of relationships between variables at different levels of analysis (e.g., individual and organizational) necessitates collection of data at each of the different levels. Oftentimes, researchers do not have a global index of the organiza