This paper surveys available techniques and introduces an explicit statement of a new statistic to test for equality of correlated proportions in a polychotomous response design. A set of guidelines for the potential user of the techniques is provided. (Author/CTM)

Problems in selection of optimal designs in item-response theory (IRT) models are resolved through a sequential design procedure that is a modification of the D-optimality procedure proposed by Wynn (1970). This algorithm leads to consistent estimates, and the errors in selecting the abilities generally do not greatly affect optimality. (SLD)

Commentary is presented on the evaluation of the Emergency School Aid Act and on an article detailing that evaluation (TM 503 672). The use of randomization and pilot studies is emphasized. (J KS)

The paper describes the small sample stability of least square estimates of variance components within the context of generalizability theory. Monte Carlo methods are used to generate data conforming to some selected multifacet generalizability designs to illustrate the sampling behavior of variance component estimates. (Author/CTM)

Rosenthan's (1979) concept of fail-safe N has thus far been applied to probability levels exclusively. This note introduces a fail-safe N for effect size. (Author)

A method is proposed for calculating the sample size needed to achieve acceptable statistical power with a given test. The minimally important difference significant (MIDS) criterion for sample size is explained and supported with recommendations for determining sample size. The MIDS criterion is computationally simple and easy to explain. (SLD)

It is shown that using formulae for the estimation of sampling errors based on simple random sampling, when a design actually involves cluster sampling, can lead to serious underestimation of error. Jackknife and balanced repeated replication are recommended as techniques for dealing with this problem. (Author/CTM)

The effects of certain characteristics (e.g., sample design) of National Assessment of Educational Progress (NAEP) data on statistical analysis techniques are considered. Ignoring special features of NAEP data and proceeding with a standard analysis can produce inferences that underestimate the true variability and overestimate the true degrees of…

Procedures for obtaining student samples for the National Assessment of Educational Progress (NAEP) and deriving survey weights for analysis of survey data are described. Sample designs are economically and operationally feasible, and weighting procedures result in increased precision of estimates as they account for the probabilities of student…

Several developments growing out of the National Assessment of Educational Progress (NAEP) are reviewed, with a discussion of their extension and application to other projects. These developments include: (1) complex matrix item sampling designs; (2) performance-based items in large-scale assessments; (3) vertical scaling; and (4) innovative…