Designs for sequential sampling procedures that adapt to cumulative information are discussed. A familiar illustration is the play-the-winner rule in which there are two treatments; after a random start, the same treatment is continued as long as each successive subject registers a success. When a failure occurs, the other treatment is used until…

A brief, practical overview of "design effects" (DEFFs) is presented for users of the results of sample surveys. The overview is intended to help such users to determine how and when to use DEFFs and to compute them correctly. DEFFs are needed only for inferential statistics, not for descriptive statistics. When the selections for…

In applied and experimental research, it has been demonstrated that the extreme groups procedure is more powerful than the standard correlational approach for some values of the correlation and extreme group size. Methods are provided for using the covariance information that is usually discarded in the classical extreme groups approach.…

In a complex sampling scheme it is desirable to select the primary sampling units (PSUs) without replacement to prevent duplications in the sample. Since the estimation of the sampling variances is more complicated when the PSUs are selected without replacement, L. Kish (1965) recommends that the variance be calculated using the formulas…

A general framework for conducting generalizability analyses is presented. Generalizability theory is extended to situations in which the objects of measurement are not persons but other factors, such as instructional objectives, stages of learning, and treatments. (Author/PN)

Bayesian statistical methodology and its possible uses in the behavioral sciences are discussed in relation to the solution of problems in both the use and teaching of fundamental statistical methods, including confidence intervals, significance tests, and sampling. The Bayesian model explains these statistical methods and offers a consistent…

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 equating methods and sampling designs used in the empirical studies in this special issue on the use of matched samples for test equating are described. Four requisites for equating are listed, and the invariance of equating functions requisite is identified as the focus of this issue. (SLD)

A generalized variance criterion is used for sequential sampling in the two-parameter item response theory model. Some principles are offered to enable the researcher to select the best sampling design for efficient estimation of item parameters. Topics include the choice of an optimality criterion, two-stage designs, and sequential designs. (SLD)

A study on sampling errors of variance components was conducted within the framework of generalizability theory by P. L. Smith (1978). The study used an intuitive approach for solving the problem of how to allocate the number of conditions to different facets in order to produce the most stable estimate of the universe score variance. Optimization…

The concepts, definitions, and notation that have evolved with the development of telephone survey design methodology are discussed and presented as a unified structure. This structure is then applied to some of the more well-known telephone survey designs and alternative designs are developed. The relative merits of the different survey designs…

A set procedure developed in this study is useful in determining sample size, based on specification of linear contrasts involving certain formula treatments. (Author/DEP)

A solution is proposed for analysis of variance procedures with missing cells, such as may occur when a control group is not assigned to any of the rows or columns of the various experimental groups. Mathematical models for two-way design are presented which define several variables; as well as row effect, column effect, and row and column…

The unbiased estimate of a "treatment effect" reached by analysis of covariance in a nonrandomized experiment would often require that a different covariate be used in each treatment. A sufficient but unlikely condition for an unbiased estimate is that the covariate for each treatment is (1) the complete covariate that predicts the outcome as…

This report describes a statistically designed experiment that was carried out in an operational setting to determine the contributions of different sources of variation to the unreliability of scoring. The experiment made novel use of partially balanced incomplete block designs that facilitated the unbiased estimation of certain main effects…