Communication and diffusion of the iucd: a case study in urban india

In this study the diffusion and adoption framework is used to investigate a family planning innovation. The study indicates the utility of this framework from an analytical point of view both for the researcher to the process by which family planning comes to be adopted, and for the administrator to understand the working of the communications elements of his program.The data indicate that different communications media and informal communications networks are used at different stages of the adoption process. At the awareness stage, messages emanating from the family planning administration make their biggest impact. At the later stages of interest and evaluation, local sources of information become important, and interaction with the clinic staff takes place at high rates.Both husbands and wives are involved in the communications processes, but they have different communication patterns. Both are also involved in the final adoption decision-making processes.     

The Identifiability of Dependent Competing Risks Models Induced by Bivariate Frailty Models

In this paper, we propose to use a special class of bivariate frailty models to study dependent censored data. The proposed models are closely linked to Archimedean copula models. We give sufficient conditions for the identifiability of this type of competing risks models. The proposed conditions are derived based on a property shared by Archimedean copula models and satisfied by several well‐known bivariate frailty models. Compared with the models studied by Heckman and Honoré and Abbring and van den Berg, our models are more restrictive but can be identified with a discrete (even finite) covariate. Under our identifiability conditions, expectation–maximization (EM) algorithm provides us with consistent estimates of the unknown parameters. Simulation studies have shown that our estimation procedure works quite well. We fit a dependent censored leukaemia data set using the Clayton copula model and end our paper with some discussions. © 2014 Board of the Foundation of the Scandinavian Journal of Statistics     

Disaggregate-level estimates of indebtedness in the state of Uttar Pradesh in India: an application of small-area estimation technique

The National Sample Survey Organisation (NSSO) surveys are the main source of official statistics in India, and generate a range of invaluable data at the macro level (e.g. state and national levels). However, the NSSO data cannot be used directly to produce reliable estimates at the micro level (e.g. district or further disaggregate level) due to small sample sizes. There is a rapidly growing demand of such micro-level statistics in India, as the country is moving from centralized to more decentralized planning system. In this article, we employ small-area estimation (SAE) techniques to derive model-based estimates of the proportion of indebted households at district or at other small-area levels in the state of Uttar Pradesh in India by linking data from the Debt–Investment Survey 2002–2003 of NSSO and the Population Census 2001 and the Agriculture Census 2003. Our results show that the model-based estimates are precise and representative. For many small areas, it is even not possible to produce estimates using sample data alone. The model-based estimates generated using SAE are still reliable for such areas. The estimates are expected to provide invaluable information to policy analysts and decision-makers.     

Determinants of Individual Giving Behavior in Urban India

This paper, based on a primary sample survey over 1925 earning individuals in the cities of Kolkata, Cuttack and Bengaluru, examines how the individual and household characteristics influence the acts of giving in urban India. The regression results indicate income, family size and property ownership affecting likelihood and extent of giving. Likelihood to give is more with females, though males tend to donate more. There exists threshold income beyond which likelihood to donate is less. Characteristics like age, education, dependency ratio and marital status influence certain acts of giving. As the opportunity cost of non-cash giving increases with the rise in income, cash donations substitute non-cash giving. There also prevails complementarity in the acts of giving. On behavioral front, in addition to work–life balance and pledging, the notion of rational choice seems to be gaining ground.

     

A Generalized Poisson Distribution

Cumulative probabilities of a Poisson distribution can be written in terms of incomplete gamma function where the parameter of the gamma function is an integer. From this definition a new generalization of the Poisson distribution is obtained with two parameters. Asymptotic behavior of this distribution is shown to be normal. Some order properties of this distribution are also studied.     

Participation in Voluntary Youth‐Serving Associations and Early Adult Voting Behavior*

Objective. We investigate adolescent membership in voluntary associations and whether participation in these activities influences voting behavior during early adulthood. Methods. Weighted logistic regression models predicting membership in voluntary associations and voting behavior were estimated using data from the National Educational Longitudinal Study of 1988–1994 (NELS). Results. Our findings suggest that membership in voluntary associations varies by race and socioeconomic status (SES). In addition, membership in organizations historically rooted in moral development and civic socialization positively predict voter‐registration status and whether or not young adults participated in the first national election that they were eligible to vote in, but this relationship is moderated by both race and SES. Conclusions. Our findings suggest that a large proportion of U.S. teenagers still participate in community‐based programs, many of which foster later civic participation, but that all youth do not equally benefit from participation.     

Modeling a low-carbon garment supply chain

This article attempts to introduce indirect carbon emission and trade-credit concept in a network optimisation model for sustainable supply chain. The proposed model optimises total cost, total direct carbon emission, total indirect emission in the form of embodied carbon footprint of the raw material and total trade-credit amount over the purchased item in a supply chain. The model calculates the total cost by considering purchasing cost, logistics cost, handling cost and manufacturing cost. It attempts to measure the direct emission involved in manufacturing and logistics operations. The model has the capability to consider dissimilar trucks used for transportation according to their operating cost and carbon emission. Multi-objective goal programming is applied to deal with four objectives to find a tradeoff among these objectives. The result suggests that managers should capture the direct as well as the indirect emission which helps in arriving at appropriate strategy for a sustainable supply chain. The effectiveness of the proposed model is demonstrated through a case of a garment supply chain. This model also supports in deciding appropriate goal for carbon emission, supply chain costs, etc.     

On removing Condorcet effects from pairwise election tallies

Condorcet profiles are responsible for a number of well known preference aggregation paradoxes. It is reasonable to claim that these profiles represent complete ties between the candidates and should therefore be excluded to determine election outcomes. Established profile decomposition techniques are of limited usefulness in extracting and removing Condorcet effects, because of the computational complexity involved, even if complete knowledge of voters’ rankings of all candidates are available. The paper discusses an easily implementable method of removing or reducing Condorcet effects from pairwise scores. Pairwise scores (and not complete knowledge of voters’ rankings) are often the only available data based on which an election winner has to be determined.     

School Context and the Effect of ESL Placement on Mexican‐Origin Adolescents' Achievement*

Objectives. Immigrant adolescents' academic achievement is crucial to our future economic stability, and Mexican‐origin linguistic minority youth in U.S. schools generally demonstrate lower levels of achievement. English as a Second Language (ESL) programs provide an institutional response to these students' needs, the effect of which may vary by the proportion of immigrant students in the school. Measures. Using propensity score matching and data from the Adolescent Health and Academic Achievement Study (AHAA) and the National Longitudinal Study of Adolescent Health (Add Health), we estimate the effect of ESL placement on Mexican‐origin achievement for first‐, second‐, and third‐generation adolescents separately in schools with many and few immigrant students. Results. The estimated effect of ESL placement varies by both immigrant concentration in the school and by students' generational status. Conclusions. We find that ESL enrollment may be protective for second‐generation Mexican‐origin adolescents in high immigrant concentration schools, and may prove detrimental for first‐generation adolescents in contexts with few other immigrant students.