Modeling the population in survey sampling problems continues to be controversial. An important reason is that the likelihood principle makes it somewhat necessary to model the population. Estimating the population total in two-stage survey sampling is considered, making use of a "superpopulation" model. The problem is then really one of…

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…

Some recent methods are presented for analyzing categorical data from complex surveys involving clustering familiar in educational research. Methods that provide first-order corrections to standard multinomial-based chi-square tests by taking into account survey design effects are highlighted. Design-based calculation techniques guarantee that the…

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…

Presents solutions for the problem of maximizing the generalizability coefficient under a budget constraint. Shows that the Cauchy-Schwarz inequality can be applied to derive optimal continuous solutions for the number of conditions of each facet. Illustrates the formal similarity between optimization problems in survey sampling and…

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)

A method for drawing inferences from complex samples is based on Rubin's approach to missing data in survey research. Standard procedures for drawing such inferences do not apply when the variables of interest are not observed directly, but must be inferred from secondary random variables which depend on the variables of interest stochastically.…

This book, one of a series prepared in connection with the Behavioral and Social Sciences Survey (BASS) conducted between 1967 and 1969, deals with problems of statistics, mathematics, and computation as they related to the social sciences. Chapter 1 shows how these subjects help in their own ways for studying learning behavior with irregular…