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)

It is argued in this paper that generalizability theory provides a uniquely useful framework for defining and quantifying the dependability of data for decision making. It does so by requiring careful specification of the conditions of measurement and the anticipated sources of variation in the results of the measurement procedure. A distinction…

Thirty-four papers on educational statistics which were presented at the 1971 AERA Conference are summarized. Six major interest areas are covered: (a) general information; (b) non-parametric methods; (c) errors of measurement and correlation techniques; (d) regression theory; (e) univariate and multivariate analysis; (f) factor analysis. (MS)