Measuring and understanding the nature of informant/rater effects and differences (Level 1) on a common trait when the target of measurement is at the organizational level (Level 2) involves a number of methodological considerations. Although previous research has discussed single-level latent variable applications of the correlated trait-correlated method minus one (CT-C(M-1)) model for multitrait-multimethod (MTMM) designs, only recently was the CT-C(M-1) model derived for multilevel data structures. The current paper examines research on the development of multilevel latent variable measurement models when both structurally different and interchangeable raters are involved in measuring Level 2 constructs. In so doing, we review and articulate often overlooked design and interpretive considerations unique to these models. We describe these elements within the context of a real-world multilevel CT-C(M-1) latent variable model that measures school climate for 294 public high schools using individual-level ratings from students (N = 58,018), teachers (N = 12,236), and health professionals (N = 742).