Abstract
A relatively recent advance in analyzing longitudinal data, structural equation modeling with structured means, for examining the impact of organizational change and development interventions, is presented. Some of the limitations of current approaches to analyzing data collected from experimental and control groups are discussed, along with why structural modeling is particularly useful for realworld experiments and quasiexperiments. An illustration is then given, applying this approach to data collected from a teambuilding intervention which involved 2,331 employees in 16 plants of a large garment manufacturer. Implications of the research are briefly considered.