Sounds of Silence: narrative research with inarticulate subjects

This article addresses the challenge of using narrative methods with people who have learning difficulties. Such informants present four particular interview problems: inarticulateness; unresponsiveness; a concrete frame of reference; and difficulties with the concept of time. The authors focus on the first two of these problems and argue that neither of them constitutes an insuperable barrier to people telling their story. Drawing on detailed interview material from an informant with learning difficulties, the authors set out to show in practical terms how these problems might be tackled, emphasising in particular the importance of being attentive to what goes unsaid. They conclude that researchers should put more emphasis on overcoming the barriers that impede the involvement of inarticulate subjects in narrative research instead of dwelling on their limitations as informants.     

Optimal control designs using predicting densities for the multivariate linear model

We provide an application of a variety of predicting densities to quality control involving multivariate normal linear models. We produce optimal control designs for single muleivaiiate future observations using predicting densities employing estimative, profile likelihood, Hinkley-Lauritzen, Butler, Bayesian, and Parametric Bootstrap methodologies. The decision-theoretic optimality criterion is an intuitively appealing quadratic consumer-producer risk function. The optimal control design arising from an optimal Kullback-Leibler frequentist prediction density is shown to coincide with that arising from an optimal Kullback-Leibler Bayesian predictive density. An example involving EVOP is provided to illustrate the methodology and to raise questions concerning the relative merics of the variety of predictive approaches in the quality control context.     

Grey Predictive Process Control Charts

The present article intends to develop some imputation methods to reduce the impact of non response at both the occasions in two-occasion successive (rotation) sampling. Utilizing the auxiliary information, which is only available at the current occasion, estimators have been proposed for estimating the population mean at the current occasion. Estimators for the current occasion are also derived as a particular case when there is non response either on the first occasion or second occasion. Behaviors of the proposed estimators are studied and their respective optimum replacement policies are also discussed. To study the effectiveness of the suggested imputation methods, performances of the proposed estimators are compared in two different situations, with and without non response. The results obtained are demonstrated with the help of empirical studies.     

Correction to: The Impact of Agricultural Technologies on Poverty and Vulnerability of Smallholders in Ethiopia: A Panel Data Analysis

Social Indicators Research - The article The Impact of Agricultural Technologies on Poverty and Vulnerability of Smallholders in Ethiopia: A Panel Data Analysis, written by Wubneshe Dessalegn Biru,...     

Restricted tests for testing independence of time to failure and cause of failure in a competing-risks model

We consider the competing-risks problem without making any assumption concerning the independence of the risks. Maximum-likelihood estimates of the cause-specific hazard rates are obtained under the condition that their ratio is monotone. We also consider the likelihood-ratio test for testing the proportionality of two cause-specific hazard rates against the alternative that the ratio of these two hazard rates is monotonic. This testing problem is equivalent to testing independence against likelihood-ratio dependence of the time to failure and the cause of failure in the competing-risks setup. We allow for random censoring on the right. The asymptotic null distribution of the test statistic is obtained and is found to be of the chi-bar-square type. The problem is extended to the case of more than two risks. A numerical example is given to illustrate the procedure.     

Marriage and Subjective Well-Being: How and Why Context Matters

Over the last 20 years the academic community has experienced a burgeoning interest in the causes and correlates of subjective well-being. One of the most consistent findings has been that married respondents report higher levels of happiness and life satisfaction than unmarried respondents. Despite its prevalence, scant empirical research has focused on the potential mechanisms driving this relationship. The current work draws on the Behavior Risk Factor Surveillance System along with 2000 US Census data to investigate the role of context and reference groups in shaping the relationship between marriage and well-being. The primary research question is whether marriage has a greater influence on life satisfaction when it is more common and thus more normative? The findings offer new insight into the marriage/well-being relationship and have broad implication for how we think about the study of the causes and correlates of subjective well-being.