The purpose of this chapter is to introduce the reader to some recent innovations intended to solve the problem of equating test scores on the basis of data from small numbers of test takers. We begin with a brief description of the problem and of the techniques that psychometricians now use in attempting to deal with it. We then describe three new approaches to the problem, each dealing with a different stage of the equating process: (1) data collection, (2) estimating the equating relationship from the data collected, and (3) using collateral information to improve the estimate. We begin with Stage 2, describing a new method of estimating the equating transformation from small-sample data. We also describe the type of research studies we are using to evaluate the effectiveness of this new method. Then we move to Stage 3, describing some procedures for using collateral information from other equatings to improve the accuracy of an equating based on small-sample data. Finally, we turn to Stage 1, describing a new data collection plan in which the new form is introduced in a series of stages rather than all at once.