Generalized symmetric means are redefined in a way which allows them to be calculated for any matrix sampling design. It is proved that these sample generalized symmetric means are unbiased estimates of the analogous population generalized symmetric means. Illustrative examples are given. (Author)

Investigated empirically through post mortem item-examinee sampling were the relative merits of two alternative procedures for allocating items to subtests in multiple matrix sampling and the feasibility of using the jackknife in approximating standard errors of estimate. The results indicate clearly that a partially balanced incomplete block…

The effect of stratified sampling of items on the estimation of test score distribution parameters by multiple matrix sampling was studied. Item difficulty and/or interitem correlations were the bases of stratification. Various item iniverses were created by computer simulation and sampled according to several plans. The results indicate that…

A single conceptual and theoretical framework for sampling any configuration of data from one or more population matrices is presented, integrating past designs and discussing implications for more general designs. The theory is based upon a generalization of the generalized symmetric mean approach for single matrix samples. (Author/CTM)

The restrictions on item difficulties that must be met when binomial models are applied to domain-referenced testing are examined. Both a deterministic and a stochastic conception of item responses are discussed with respect to difficulty and Guttman-type items. (Author/BH)

Empirical evidence is presented related to the effects of using a stratified sampling of items in multiple matrix sampling on the accuracy of estimates of the population mean. Data were obtained from a sample of 600 high school students for a 36-item mathematics test and a 40-item vocabulary test, both subtests of the Iowa Tests of Educational…