An efficient new randomized response model

This paper addresses the problem of estimating the population proportion π of a sensitive group. We have suggested a randomized response (RR) model that is more efficient than the one envisaged by Gjestvang and Singh ([2006), A new randomized response model, Journal of Royal Statistcal Socity, B, (3), 523–530].     

The Rising Burden of Healthcare Expenditure in India: A Poverty Nexus

The increasing burden of communicable and non-communicable diseases are imposing unavoidable costs on Indians. As a consequence it exacerbate poverty and drag many poor further down by heavy medical expenses. This study aims to estimate the extent of healthcare expenditure on the individuals who were hospitalized due to various diseases. Further, this study examines the burden of healthcare expenditure on impoverishment level in India. The unit level record of the 71st round of the National Sample Survey Office (NSSO) is used in the analysis. The result reveals, cost of hospitalization due to non-communicable diseases is three times higher than communicable diseases in India. Therefore, an overall level of impoverishment has been increased by 1.61 percent/year which shows the high financial risk for the people surviving at the threshold of poverty.     

A class of chain ratio–product type estimators with two auxiliary variables under double sampling scheme

In this paper, a chain ratio–product type estimators has been developed for estimating population mean of the study variable using two auxiliary variables under double sampling scheme, when the information on another additional auxiliary character is available along with the main auxiliary character. The optimum property of the proposed strategy has been identified in two different cases with their variances. Theoretical and empirical studies have been done to demonstrate the efficiency of the proposed estimator over other estimators, which utilized the information on two auxiliary characteristics.     

Orthogonally blocked mixture component–amount designs via projections of F-squares

Orthogonal block designs for Scheffé’s quadratic model have been considered previously by Draper et al. (1993), John (1984), Lewis et al. (1994) and Prescott, Draper, Dean, and Lewis (1993). Prescott and Draper (2004) obtained mixture component–amount designs via projections of standard mixture designs, viz., the simplex-lattice, the simplex-centroid and the orthogonally blocked mixture designs based on latin squares. Aggarwal, Singh, Sarin, and Husain (2009) considered the case of components assuming equal volume fractions and obtained mixture designs in orthogonal blocks using F-squares. In this paper, we construct orthogonal blocks of two and three mixture component–amount blends by projecting the class of four component mixture designs presented by Aggarwal et al. (2009).     

“It's Complicated”: Collective Memories of Transgender,Queer, and Questioning Youth in High School

Using the qualitative participatory action methodology, collective memory work, this study explored how transgender, queer, and questioning (TQQ) youth make meaning of their sexual orientation and gender identity through high school experiences. Researchers identified three major conceptual but overlapping themes from the data generated in the transgender, queer, and questioning youth focus group: a need for resilience, you should be able to be safe, and this is what action looks like! The researchers discuss how as a research product, a documentary can effectively “capture voices” of participants, making research accessible and attractive to parents, practitioners, policy makers, and participants.     

DDMA-charts: Nonparametric multivariate moving average control charts based on data depth

Summary: This paper studies the DDMA–chart, a data depth based moving–average control chart for monitoring multivariate data. This chart is nonparametric and it can detect simultaneously location and scale changes in the process. It improves upon the existing r– and Q–chart in the efficiency of detecting location changes. Both theoretical justifications and simulation studies are provided. Comparisons with some existing multivariate control charts via simulation results are also provided. Some applications of the DDMA–chart to the analysis of airline performance data (collected by the FAA) are demonstrated. The results indicate that the DDMA–chart is an effective nonparametric multivariate control chart.*Research supported in part by grants from the National Science Foundation, the National Security Agency, and the Federal Aviation Administration. The discussion on aviation safety in this paper reects the views of the authors, who are solely responsible for the accuracy of the analysis results presented herein, and does not necessarily reect the official view or policy of the FAA. The dataset used in this paper has been partially masked in order to protect confidentiality.     

NAFTA and labor: A Canadian perspective

The North American Agreement on Free Trade (NAFTA) has stirred passionate debates in Canada. Proponents predicted that increased trade liberalization would create more jobs, greater multinational investment, and an overall better standard of living. Opponents, however, argued that NAFTA would lead to wage cuts, job losses, the erosion of labor standards, and the harmonization of labor laws to the lowest common denominator. I systematically examined the evidence and found that with some exceptions, the predicted negative effects have not materialized. Furthermore, the NAFTA labor side agreement has enjoyed moderate success in bringing labor concerns to the fore. This paper is part of a larger project on NAFTA and Industrial Relations done with Roy J. Adams (McMaster University). I am very grateful for his insightful views and assistance. I also thank Frantz-Pierre Jerome, Senior Policy and Program Officer at the Canadian NAO, for reviewing a previous draft of this article.     

On the exact distribution of the likelihood ratio criterion for testing

The exact null distribution of the likelihood ratio criter- 2 ion for testing the hypothesis H: y = y~; z = a I, a unknown and UQ a given known vector against the alternative A =f H in a p-vari- ate normal population N (y,z) has been derived in the form of Meijer's G-function using mellin integral transform and also in a chisquare series form. Asymptotic behavior of the distribution of -2 log L has also been discussed. Percentage points for p=2(l)10for various level of significance and various degrees of freedom have been computed, but only selected tables have been presented in this paper.     

An Empirical Likelihood Estimate of the Finite Population Correlation Coefficient

In this article, the problem of the estimation of finite population correlation coefficient is considered using the empirical likelihood method. A new estimator that makes the use of both the known mean and variance of an auxiliary variable is proposed. The percent relative bias and percent relative efficiency of the proposed new estimator with respect to the usual estimator of the correlation coefficient is investigated through extensive simulation study for values of the correlation coefficient from ?0.90 to +0.90. The proposed estimator is found to perform better than the simple correlation coefficient from both the bias and relative efficiency points of views, for the population, considered in the investigation. At the end, the proposed estimator has been extended to complex survey designs. Supplementary materials for this article are available online.     

Estimation of Ratio of Two Finite-Population Means in the Presence of Non Response

It is well known that a ranked set sample under perfect ranking provides more information than an i.i.d. sample of the same size. Then it may be interesting to study how much information is lost due to imperfect ranking. In this article, we consider some ranking mechanisms and study the loss of the Fisher information according to the degree of imperfect ranking. Then we continue to discuss the optimal combination of the sample size and number of strata in terms of maximizing the Fisher information for the bivariate normal and exponential distributions.