We present types of constructs, individual- and cluster-level, and their confirmatory factor analytic validation models when data are from individuals nested within clusters. When a construct is theoretically individual level, spurious construct-irrelevant dependency in the data may appear to signal cluster-level dependency; in such cases, however, and consistent with theory, a single-level analysis with a correction for dependency may be appropriate. Regarding cluster-level constructs, we discuss two types--shared and configural--and present appropriate validation models. Illustrative validation analyses with individual, shared, and configural constructs are provided using empirical data as well as simple simulations demonstrating the spurious effects that can occur with nested data. The article concludes with future directions to be examined in construct validation in multilevel settings.