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Abstract: Often, in biomedical research, where there is scientific interest in estimating the association between predictors and a binary outcome, the binary outcome is measured with uncertainty. For example, clinical outcomes are often assessed with diagnostic tests with imperfect sensitivity and specificity. Or, as another example, outcomes of a smoking cessation program might be assessed based on self-report, with accuracy subject to some doubt. In this talk, it is shown that a likelihood approach can be used to incorporate assumptions about the accuracy of the outcome measurement in the estimation of associations with predictors. Closed-form formulas for estimating odds ratios and risk ratios from 2-by-2 tables will be presented. An E-M algorithm for fitting logistic regression models with uncertain outcomes will be described. An extension of the method to the situation when there are multiple imperfect measurements of an outcome of interest will also be described. Several examples will be presented and the results of the method will be compared to those obtained using methods which ignore the imperfect measurement. A SAS macro which implements the method will be made available.
Abstract: This presentation reviews the recent rebirth of the stochastic approach to index number theory. The earlier contributions of Jevons, Edgeworth, and Bowley are also reviewed. The stochastic approach treats each price relative as an estimate of the amount of inflation between the base period and the current period. By averaging these price relatives, a more accurate estimate of price change is obtained and a confidence interval for the amount of inflation can be derived. Four criticisms of the stochastic approach are presented and assessed, including, most basically, Keynes' assertion that price relatives must be weighted according to their economic importance. The test or economic approaches to index number theory provide a basis for determining the precise nature of the weights.
Abstract: The Department of Housing and Urban Development (HUD) seeks to expand the research and policy analysis of the characteristics of recipients of assisted housing. To accomplish this, HUD has developed procedures to release household level data to researchers. While individual households are not directly identified, thecontent of the data possibly could be matched with other data sources to identify individuals. For this reason, the researchers receiving the data must agree not to release the data to others. Also, statistical disclosure limitation techniques are applied to the data to reduce the possibility of identification. This presentation will describe the process HUD went through to make these data available. This includes: 1)achieving internal agreement on the appropriate level of detail; 2) preparing a routine use statement for public comment; 3) testing the actual data for identifiability; and 4) applying statistical disclosure limitation techniques to mask identities.
Abstract: In the current issue of The American Statistician (November, 1998), McCullough proposes a methodology for assessing the reliability of statistical software on three fronts: estimation, random number generation, and statistical distributions (e.g., for calculating p-values). Results of applying this methodology to several packages will be presented: SAS, SPSS, S-PLUS, EViews, LIMDEP, SHAZAM, TSP, and EXCEL. No package scores perfectly, and some packages are decidedly better than others. Time permitting, additional benchmark results will be presented for: Wilkinson's Tests; and the Fiorentini-Calzolari-Panattoni benchmark for GARCH estimation. Again, some packages are decidedly better than others.
Using operations research techniques can help minimize these and other costs related to the management of survey operations. Operations research techniques have been used to a great extent by the military, manufacturing, and healthcare organizations. However, these methods have not been extensively applied in the field of survey research. This paper explores the potential use of operations research methods in determining training sites and allocating FRs and trainers such that costs are minimized.
OMB recently distributed for comment draft provisional guidance on the implementation of the 1997 standards for the collection of federal data on race and ethnicity. The guidance focuses on three areas: data collection, data tabulation, and methods to conduct trend analysis using data collected under both the old and the new standards. An overview of the alternatives suggested in the provisional guidance will be presented and continued research efforts will be described.
The Early Childhood Longitudinal Study -- Birth Cohort 2000 (ECLS-B) is a new project created by the National Center for Education Statistics in collaboration with other federal agencies. It is designed to provide detailed information about children's early life experiences. The ECLS-B looks at children's health, development, care, and education during the formative years from birth through first grade. This session will discuss 3 aspects of bringing the project into being: (1) Crafting working relationships with many other agencies that have strong interests in children's issues (NCHS, NIH, USDA, ACYF, MCHB, OSEP, etc.) to forge a joint approach that takes many policy interests into account within the ECLS-B framework; (2) issues in designing a sample of newborns, including research on sampling by occurrence versus residence and quantifying the relative inefficiencies of using existing PSU samples, and the mathematical programming approach to sample allocation given three domains created by the analytic subgroups; and (3) technical challenges in survey operations -- incorporating computer-assisted personal interviewing (CAPI) with direct assessments of infants and toddlers, addressing longitudinal issues from the outset of the project design, collecting data from non-resident fathers, conducting experiments on the relative effects of cash and non-cash incentives, and training lay field staff to perform non-traditional survey activities.
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