Monitoring school performance increasingly uses sophisticated analytical techniques. This document investigates whether one such method, hierarchical growth modeling, yields consistent school performance results when different metrics are used as the outcome variable. It is examined as to whether statistical and substantive inferences are altered when using normal curve equivalents (NCEs) versus scale scores. The results indicate that the effect of the metric depends upon the evaluation objective. NCEs significantly underestimate absolute growth, but NCEs and scale scores yield highly correlated (0.9) results based on mean initial status and growth estimates. Correlations between NCE and scale score rankings, based on fitted school initial status and growth values are generally over 0.94. Statistical and substantive results, using NCEs and scale scores, pertaining to school-wide program effects are highly correlated (0.95). NCEs and scale scores matched 99% of the time on whether or not the program indicator variable was statistically significant.