This paper introduces the projection methods for describing and testin
g the differences between pairs of continuous distributions, These met
hods include the projection plot, the projection spline, and the iter-
1 test. The projection plot displays the difference between correspond
ing quantiles against the average of the corresponding quantiles. It i
s analogous to an empirical quantile-quantile plot that has been rotat
ed 45 degrees. The projection spline is a knotted linear spline iterat
ively fit to the projection plot so that all knots are associated with
Significant changes in slope. It summarizes nonrandom deviations from
linearity on the projection plot, allowing classification of the high
est level of difference between two distributions as a difference in s
hape, in spread, or in location. The iter-1 test compares the first it
eration of the projection spline with the line y = 0, providing a glob
al test of difference between two distributions that is more powerful
in simulations than either the chi-square test of independence or the
Kolmogorov-Smirnov test. These methods will enhance epidemiologic prac
tice by making the comparison of full distributions an accessible tool
for routine data analysis.