Osteological studies both old and new have utilized various Polynesian cranial samples, individually or in combination, to assess the racial composition of prehistoric Polynesians as a group, with regards to other Pacific populations, or to represent the Polynesian peoples as a whole in various multivariate analyses of worldwide populations. However, few of these studies have assessed the degree of intrasample variation produced when data derived from skeletal samples from different Polynesian islands (populations) are pooled to represent "Polynesians" as a whole. A similar argument can be made when data derived from various museum skeletal samples of the same Polynesian population are pooled to produce a larger sample representing that particular Polynesian population (Murrill [1968] Cranial and postcranial skeletal remains from Easter Island; Minneapolis: University of Minnesota Press; Stefan [2002] Am. J. Phys. Anthropol. [Suppl.] 34:147). This study examined Easter Island crania curated at various museums in North America, South America, and Europe to assess whether significant differences exist among the museum collections of Rapa Nui (Easter Island) skeletal material. A NORM statistical program (Schafer and Olsen [1997] NORM, version 1.01; University Park: Pennsylvania State University) for multiple imputation of incomplete multivariate datasets was utilized to estimate missing data. A variance comparison method, which utilizes variance/covariance matrices derived from "hypothesis" and "baseline/reference" samples (Key and Jantz [1990] Hum. Evol. 5:457-469; Key and Jantz [1990] Am. J. Phys. Anthropol. 82:53-59) was used to compare the Rapa Nui museum samples. This method is designed to test whether variability in a "hypothesis" museum sample exceeds "normal within-group variability" represented by the "baseline/reference" sample. The method was applied to six Rapa Nui museum samples (AANMW, MNHN-KB, MNHN-NAE, NHM, MH, and AMNH). The results indicate that the museum "hypothesis," male and female samples, exhibited little intrasample variability from the "baseline/reference" sample (MAPSE), though the samples were collected at different times and by different individuals. These results show the ability of multiple imputation and variance comparison methodologies to predict missing variables while maintaining the inherent variance/covariance structure and to discriminate sample variation in artificially assembled samples.