To compare the “bang for the buck” in receive performance versus introductory price, my NCJ articles took the approach of creating a ratio of composite Rx performance divided by price in inflation-adjusted 2019 dollars. But since the dollar metric would give some non-intuitive numbers as the SPI is in a metric of an average of 100 (sd = 15), I put price into a similar metric that is more user-friendly to (non-statistician) viewers.
Using a T-score transformation for rig Price upon market entry (mean = 100, sd = 15), I created a ratio of the Sherwood Performance Index (SPI) to price. Thus, a ratio of 1.0 means that the rig is exactly average on price in 2021 dollars and the SPI. Over 1.0, the ratio indicates a higher Rx bang-for-the-buck while less than 1.0 suggests the opposite. I call this the Performance-for-Price Ratio (PPR). There may be reasons for the higher or lower ratios in terms of features and such not in the SPI, so keep that in mind. This is a guide, not a decision-maker on it’s own. Keep in mind, the performance here is only Rx performance. A rig with a lower PPR might be a better overall rig but you’ll have to ascertain that via additional scrutiny of features, Tx performance, and so forth.
In the scatterplot below, I’ve shown the trend in composite Rx performance with market-entry price held constant. The range slider at the bottom allows the viewer to move the left or right (or both) sliders to identify subsets of rigs for further detailed scrutiny. The most frequent use for this is likely to restrict the plot to more recently introduced rigs so as to identify rig Rx performance for the price. But this is up to the viewer’s desires for interrogating these data.