Benjamin J. Tepping

A Model for Optimum Linkage of Records

Abstract A model is presented for the frequently recurring problem of linking records from two lists. The criterion for an optimum decision rule is taken to be the minimization of the expected total costs associated with the various actions that may be taken for each pair of records that may be compared. A procedure is described for estimating parameters of the model and for successively improving the decision rule. Illustrative results for an application to a file maintenance problem are given.

The Development of Sample Surveys of Finite Populations

This paper discusses selected topics in the theory and methods of sample surveys which have as their objectives to provide inferences about some characteristics of a finite population (as distinguished from inferences about a causal system which may have produced certain characteristics of the finite population). The paper gives an account of some early developments, considers criteria to guide the choice of sample design, and considers various aspects of probability-sampling designs, including nonsampling error and total survey design. Finally, the paper discusses the role of models in the theory and practice of sample surveys for making inferences about a finite population, and lists some areas for research and development.

Regression Estimates in Federal Welfare Quality Control Programs

Abstract States that administer federal family welfare programs review samples of the beneficiaries to guide corrective actions. Federal agencies review subsamples of the state samples to compute overpayment error rates using a regression estimator. These federal estimates make state-to-state comparisons of quality possible and are also used for fiscal sanctions. Such applications of the regression estimator have been widely challenged. We show that the regression estimates and estimates of their variances are closely unbiased, and we examine their statistical characteristics. We also comment on the recent reports of the National Research Council Panel on Quality Control of Family Assistance Programs.

Variance Estimation for a Specified Multiple-Frame Survey Design

This paper is concerned with the estimation of the variance of estimates based on a multiple-frame sample design in which alphabetic clusters of elements have been sampled from different lists, and where elements selected from different lists may correspond to the same element of the population of interest. A nesting procedure is used to assure that clusters selected from any one of the lists are also in the sample for any other list in which an equal or greater sampling rate has been specified.