This study investigates the population sensitivity of the commonly used linear equating methods in the Non-Equivalent-groups with an Anchor Test (NEAT) design: the Tucker, the Levine observed-score, and the chain linear methods. For a detailed analysis of the subject, we apply three distinctive approaches to a real data set from a NEAT design: a) the RMSD index for the NEAT design of von Davier, Holland, and Thayer (2004); b) the parallel-linking system of Dorans and Holland (2000), and c) the pseudo-NEAT design approach of von Davier, Holland, and Thayer (2003). The data set is used to illustrate the derivations on male and female subpopulations. Comparisons of the results obtained using linear and equipercentile equating are also presented. For this particular data set the Levine function seems to vary less across subpopulations than the other methods; the Tucker method seems to vary the most.