The purpose of this study was to evaluate the sensitivity of growth and value-added modeling to the way an underlying vertical score scale has been created. Longitudinal item-level data were analyzed with both student- and school-level identifiers for the entire state of Colorado between 2003 and 2006. Eight different vertical scales were established on the basis of choices made for three key variables: the item response theory modeling approach, the calibration approach, and the student proficiency estimation approach. Each scale represented a methodological approach that was psychometrically defensible. Longitudinal values from each scale were used as the outcome in a commonly used value-added model (the "layered model" popularized by William Sanders) as a means of estimating school effects. Our findings suggest that while the ordering of estimating school effects is insensitive to the underlying vertical scale, the precision of such value-added estimates can be quite sensitive to the combinations of choices made in the creation of the scale.