Protonorms are generalized raw scores that allow comparison between scores on all of the tests, but do not contain information as to where that score stands in any population. They are not standard scores or quantiles, and do not have a fixed mean and standard deviation. Protonorms are established by rank-equating the shared scores (that is, the scores from the same group of candidates) on each combination of two tests, resulting in, as it were, "raw scores" on a hypothetical test with finer resolution than have most of the individual tests. Protonorms can be normed to proportions outscored, I.Q.s, or other standard scores by combining the data from several tests, thus using many more data points than when each test is normed by itself and therefore reducing the need for interpolation and extrapolation. Also, the relation between protonorms and those other scores can be reassessed and adjusted from time to time without needing to update all of the existing norm tables of the individual tests; only one table needs to be changed instead of many.
Conceptually, protonorms can be considered raw scores on a hypothetical high-range test with very many items (say around a thousand) dimensioned such that no one can solve them all, the smartest individuals can solve roughly three fourths of them, and the least able high-range candidates can solve less than one tenth of them.