A perspective of composite sampling

Composite samples are formed by physically mixing samples. Usually, composite samples are used to reduce the overall cost associated with analytical procedures that must be performed on each sample, but they can also be used to protect the privacy of individuals.

Composite sampling can reduce the cost of identifying individual cases that have a certain trait, such as those with a rare disease or those exceeding pollution-level standards. Not much is lost by applying this method as long as the trait is relatively rare.

Composite sampling can reduce the cost of estimating the mean of some process. When samples are composited, the ability to estimate the variance is lost. In spite of this, the potential savings are so great that composite samples have been used.

Much of this paper deasl with the variance of estimators based on composite sampling when the porportions of hte original samples comprising the composite sample are actually random. Taking repeated samples and measurements on several composite samples complicates the prodcedure, but allows the estimation of between and within variation as well as measurement error.     

Testing parameter of the power series distribution of a zero inflated power series model

The Zero Inflated Power Series Distribution (ZIPSD) contains two parameters. The first parameter indicates inflation of zero and the other parameter is that of the Power Series distribution. We provide three asymptotic tests for testing the parameter of Power Series distribution, using an unconditional (standard) likelihood approach, a conditional likelihood approach and a test based on sample mean, respectively. The performance of these three tests has been studied for Zero Inflated Poisson Distribution (ZIPD). Asymptotic Confidence Intervals for the parameter are also provided.     

On additive and multiplicative damage models and the characterizations of linear and logarithmic exponential families

Rao (1963) has formulated a damage model which we call an additive damage model. A suitable damage model, which we call a multiplicative damage model, has been considered by Krishnaji (1970) for income-related problems. In these models, an original observation is subjected to damage, e.g., death or under-reporting, according to a specified probability law. Within the framework of an additive damage model, with a special form of damage, characterizations of the linear and logarithmic exponential families are formulated using regression properties of the damaged part on the undamaged part. The characterizations of the gamma and Pareto distributions that have been found of some use in the theory of income distributions, are obtained as special cases. Similar results are investigated within the framework of the multiplicative damage model.     

Variable Bandwidths for Nonparametric Hazard Rate Estimation

A smoothing parameter inversely proportional to the square root of the true density is known to produce kernel estimates of the density having faster bias rate of convergence. We show that in the case of kernel-based nonparametric hazard rate estimation, a smoothing parameter inversely proportional to the square root of the true hazard rate leads to a mean square error rate of order n ^?8/9, an improvement over the standard second order kernel. An adaptive version of such a procedure is considered and analyzed.     

Tests for Equality of Inflation Parameters of Two Zero-Inflated Power Series Distributions

In this article, we consider two independent zero-inflated power series distributions and provide likelihood ratio test for equality of inflation parameters of the same. As an illustration, testing equality of inflation parameters of two zero inflated Poisson distributions is provided. Further, simulation study to investigate power of likelihood ratio tests has been carried out.     

Invariance of linearity of regression and related characterizations of some classical discrete distributions

Rao (1963) introduced what we call an additive damage model. In this model, original observation is subjected to damage according to a specified probability law by the survival distribution. In this paper, we consider a bivariate observation with second component subjected to damage. Using the invariance of linearity of regression of the first component on the second under the transition of the second component from the original to the damaged state, we obtain the characterizations of the Poisson, binomial and negative binomial distributions within the framework of the additive damage model.     

Fishery and Forestry Management

There are a large number of different definitions used for sample quantiles in statistical computer packages. Often within the same package one definition will be used to compute a quantile explicitly, while other definitions may be used when producing a boxplot, a probability plot, or a QQ plot. We compare the most commonly implemented sample quantile definitions by writing them in a common notation and investigating their motivation and some of their properties. We argue that there is a need to adopt a standard definition for sample quantiles so that the same answers are produced by different packages and within each package. We conclude by recommending that the median-unbiased estimator be used because it has most of the desirable properties of a quantile estimator and can be defined independently of the underlying distribution.     

Unhealthy Weight in Indian Families: The Role of the Family Environment in the Context of the Nutrition Transition

India faces a dual burden of increasing obesity and persistent underweight as it experiences the nutrition transition—the dietary and lifestyle changes that accompany globalization, economic development, and technological change. Yet, the nutrition transition is not solely a top-down process; rather, global forces converge with local practices at multiple levels of the social ecology. The family environment, a key site for the transmission of local customs and norms, remains largely unexplored in India. We examined the extent to which opposite-gender siblings and mother–child pairs were concordant or discordant in body weight, and whether domains of the family environment, specifically, food practices, food-related gender norms, and household resources, were associated with patterns of unhealthy weight within and between families. Multilevel dyadic analysis and logistic regression were conducted using survey data from a representative sample of 400 families in a Southern Indian city. We identified substantial clustering of weight among opposite-gender sibling pairs (ICC = 0.43) and mother–child pairs, as well as important patterns of discordance, including 11% of families experiencing a dual burden of underweight and overweight. Household resources, including mother’s education and income, were salient in explaining the distribution of body weight within and between families. Importantly, less examined domains of the family environment were also relevant, including food practices (e.g., grocery shopping frequency), and food-related gender norms (e.g., mother’s control of food served at home). Continued exploration of how global and local practices converge in households will be necessary to develop programming that effectively addresses India’s dual burden of unhealthy weight.     

On the Contributions of Cognitive Sociology to the Sociological Study of Race

In this article, we argue for cognitive sociology as a framework for studying the sociology of race. Cognitive sociology concerns itself with classification, identity construction, meaning and collective memory and is thus centrally concerned with generic issues that apply well to racial category construction and maintenance. We, first, outline the cognitive sociology framework. We then elaborate on traditions in the sociology of race and racism that have implicit affinities to cognitive sociology. We argue that cognitive sociology provides a useful generic framework with which to look at specific issues in racial classification, the social construction of race, and to racist cognitions, while critical race theory and other sociology of race frameworks can compliment cognitive sociology by addressing issues of power and domination in cognitive frameworks.     

Is failure to raise concerns about misconduct a breach of integrity? Researchers’ reflections on reporting misconduct

This article describes and discusses the views of researchers on the significance of raising concerns about scientific misconduct in their work environment and the reasons or circumstances that might deter them from doing so. In this exploratory qualitative research study, we conducted in-depth interviews with 33 researchers working in life sciences and medicine. They represent three seniority levels and five universities across Switzerland. A large majority of respondents in this research study argued that failure to raise concerns about scientific misconduct compromises research integrity. This is an encouraging result demonstrating that researchers try to adhere to high ethical standards. However, further interaction with respondents highlighted that this correct ethical assessment does not lead researchers to take the consequent action of raising concerns. The factors that discourage researchers from raising concerns need to be addressed at the level of research groups, institutions, and by setting a positive precedent which helps them to believe in the system’s ability to investigate concerns raised in a timely and professional manner. Training of researchers in research integrity related issues will have limited utility unless it is coupled with the creation of research culture where raising concerns is a standard practice of scientific and research activities.