This paper focuses on interpreting the major conceptual features of California's Academic Performance Index (API) as a coherent set of statistical procedures. To facilitate a characterization of its statistical properties, the paper casts the index as a simple weighted average of the subjective worth of students' normative performance and presents its estimation in the form of a linear model. The paper also illustrates several problems with this index for the study of a schools year-to-year progress. In current use, the API lacks realistic estimates of precision and, on closer examination, is seen to misrepresent student and school performance conceptually. The paper presents an alternative analysis of the API index, based on a Bayesian meta-analysis of results from school-specific multilevel models of longitudinal student test scores. A display is introduced for the precision of estimated relative gains of each school in the form of a profile that represents the probability that a gain estimate exceeds set fractions of the distance the pretest is from the statewide target of 800. Along with estimates of their reliabilities, researchers also produced rank estimates of school API gains rather than simply ranking schools. The approach is illustrated with an elementary school cohort who too the Stanford 9 at the Long Beach Unified School District in spring 2000. An appendix contains a method for inference on the Public Schools Accountability Act ratio. (Contains 6 tables, 6 figures, and 58 references.) (Author/SLD)