A question of identity

The weight to be attached to DNA profile evidence was the centre of a huge scientific controversy in the early-mid-1990s, with scientists, including statistical scientists, criticising each other over both science and conduct in the editorials of prestigious journals, on television and radio, and in newspapers. Today, only the occasional shot rings out on the DNA evidence front. David Balding looks back and reflects on the causes of the dispute, its evolution and resolution, and the role in it of statistics and statisticians.     

A stratified unrelated question randomized response model

This paper presents a new randomized response model that combines Kim and Warde's (2004) stratified Warner's randomized response technique using optimal allocation with the unrelated question randomized response model. The empirical studies performed show that, for the prior information given, the new model is more efficient in terms of variance (in the case of completely truthful reporting) and mean square error (in the case of less than completely truthful reporting) than its component models.     

A new unrelated question randomized response model

In this paper, we extend the work of Gjestvang and Singh [A new randomized response model, J. R. Statist. Soc. Ser. B (Methodological) 68 (2006), pp. 523–530] to propose a new unrelated question randomized response model that can be used for any sampling scheme. The interesting thing is that the estimator based on one sample is free from the use of known proportion of an unrelated character, unlike Horvitz et al. [The unrelated question randomized response model, Social Statistics Section, Proceedings of the American Statistical Association, 1967, pp. 65–72], Greenberg et al. [The unrelated question randomized response model: Theoretical framework, J. Amer. Statist. Assoc. 64 (1969), pp. 520–539] and Mangat et al. [An improved unrelated question randomized response strategy, Calcutta Statist. Assoc. Bull. 42 (1992), pp. 167–168] models. The relative efficiency of the proposed model with respect to the existing competitors has been studied.     

A sinuous stratified unrelated question randomized response model

ABSTRACT

This paper considers the use of stratified random sampling with proportional as well as Neyman allocations to unrelated question randomized response strategy. It has been shown that, for the prior information given, our new model is more efficient in terms of variance (in the case of completely truthful reporting) and mean square error (in case of less than completely truthful reporting). Numerical illustrations are also given in support of the present study.     

A modified unrelated question randomized response device for complex surveys

Singh et al. (Stat Trans 6(4):515–522, 2003) proposed a modified unrelated question procedure and they also demonstrated that the modified procedure is capable of producing a more efficient estimator of the population parameter π _A , namely, the proportion of persons in a community bearing a sensitive character A when π _A  < 0.50. The development of Singh et al. (Stat Trans 6(4):515–522, 2003) is based on simple random samples with replacement and on the assumption that π _B , namely, the proportion of individuals bearing an unrelated innocuous character B is known. Due to these limitations, Singh et al.’s (Stat Trans 6(4):515–522, 2003) procedure cannot be used in practical surveys where usually the sample units are chosen with varying selection probabilities. In this article, following Singh et al. (Stat Trans 6(4):515–522, 2003) we propose an alternative RR procedure assuming that the population units are sampled with unequal selection probabilities and that the value of π _B is unknown. A numerical example comparing the performance of the proposed RR procedure under alternative sampling designs is also reported.     

A stratified unrelated question randomized response model using Neyman allocation

This paper applies stratified random sampling using Neyman allocation to Mangat et al. (1992 Mangat, N.S., Singh, R., Singh, S. (1992). An improved unrelated question randomized response strategy. Cal. Stat. Assoc. Bull. 42:277–281.[Crossref] , [Google Scholar]) unrelated question randomized response (RR) strategy for both completely truthful reporting and less than completely truthful reporting. It is shown that, for the prior information given, our new model is more efficient in terms of variance (in the case of completely truthful reporting) and mean square error (in terms of less than completely truthful reporting) than Kim and Elam's (2007 Kim, J.M., Elam, M.E. (2007). A stratified unrelated question randomized response model. Stat. Papers 48:215–233.[Crossref], [Web of Science ®] , [Google Scholar]) model. Numerical illustrations and graphs are also given in support of the present study.     

John F. Kennedy Space Center Library

The National Aeronautics and Space Administration (NASA) John F. Kennedy Space Center Library serves most of the employees who work at the Kennedy Space Center (KSC). The archives are part of the library and contain over four million items pertaining to institutional activities within the KSC. The library collects a wide array of materials that support the work at the center. This is one of ten NASA center libraries in the country, and the focus of the collection is engineering, science, and technology. The purpose of the archives is to document the history of this center. The collection includes planning documents, photographs, and 16 mm film. The library provides its users with monographs, technical reports, databases, and both print and online journals.