Resampling method to estimate intra-cluster correlation for clustered binary data

ABSTRACT

Various methods have been proposed to estimate intra-cluster correlation coefficients (ICCs) for correlated binary data, and many are very sensitive to the type of design and underlying distributional assumptions. We proposed a new method to estimate ICC and its 95% confidence intervals based on resampling principles and U-statistics, where we resampled with replacement pairs of individuals from within and between clusters. We concluded from our simulation study that the resampling-based estimates approximate the population ICC more precisely than the analysis of variance and method of moments techniques for different event rates, varying number of clusters, and cluster sizes.     

Bayesian Inferences and Forecasts With Multiple Autoregressive Moving Average Models

The main objective of this paper is to develop convenient Bayesian techniques for estimation and forecasting which can be used to analyze multiple (multivariate) autoregressive moving average processes. Based on the conditional likelihood function and the least squares estimates of the residuals, the marginal posterior distribution of the coefficients of the model is approximated by a matrix t distribution, the marginal posterior distribution of the precision matrix is approximated by a Wishart distribution, and the predictive distribution is approximated by a multivariate t distribution. Some numerical examples are given to demonstrate the idea of using the proposed techniques to analyze different types of multiple ARMA models.     

Inference and prediction with arma processes

An essential ingredient of any time series analysis is the estimation of the model parameters and the forecasting of future observations. This investigation takes a Bayesian approach to the analysis of time series by making inferences of the model parameters from the posterior distribution and forecasting from the predictive distribution.

The foundation of the approach is to approximate the condi-tional likelihood by a normal-gamma distribution on the parameter space. The techniques illustrated with many examples of ARMA processes.     

A Superstructure of Process Capability Indices for Circular Specification Region

Circular specification regions can be seen in processes like hitting a target (in ballistics), drilling a hole (in manufacturing industries) and so on. However, only a few process capability indices are available in the literature to address the problem. Most of these indices, in turn, make some assumptions like equality of variance and independence of the two axes of the circular tolerance region. Since, in most of the cases, these assumptions are not practically viable, in the present article, we have proposed a few of the process capability indices which do not need the above assumptions to be valid. Also, we propose a superstructure which unifies all the proposed indices. Some properties of these indices have been studied including the threshold value and the relationship of the proportion of non-conformance with the member indices of the superstructure. These strengthen the practical utility of the superstructure. Distributional properties like expectations and variances of the member indices of the superstructure are also studied to have a better insight about the indices. A real life example has been discussed to carry out a comparative study of the performance of the existing as well as the newly developed indices.     

A new generalization of the gamma distribution with application to negatively skewed survival data

We propose a three-parameter distribution referred to as the reflected- shifted-truncated gamma (RSTG) distribution to model negatively skewed data. Various properties of the proposed distribution are derived. The estimation of the model parameters is approached by maximum likelihood methods and the observed information matrix is derived. Monte Carlo simulations are performed to compare the performances of the proposed methods of estimation for both small and large samples. Using information theoretic criteria, we compare the RSTG distribution to the exponential, generalized F, generalized gamma, Gompertz, log-logistic, lognormal, Rayleigh, and Weibull distributions in three negatively skewed real datasets.     

RESERVE PRICE VERSUS ENTRY FEE IN STANDARD AUCTIONS

Analysis of standard auction rules when bidders are risk averse is usually carried out under the assumption that the seller is able to set an optimal reserve. The role of entry fees has been generally overlooked in that analysis. We consider bidders with constant absolute risk aversion and show that reserve price is an essential tool in the second price auction while entry fee is essential in the first price auction. Furthermore, setting a reserve price and entry fee combination optimally may change some of the rankings of the standard auctions that hold under optimal reserves. (JEL D44)     

Urban college student self-report of hookah use with health care providers

Objective: This study's purpose was to describe urban college students’ communication about hookah with health care providers. Participants: Participants included a random sample of undergraduate urban college students and health care providers. Methods: Students surveyed determined the epidemiology of hookah use in this population, how many health care providers asked about hookah, and how many students admitted hookah use to a physician. Results: Of 375 students surveyed, 78 (20.8%) had never tried it, 284 (75.7%) had smoked hookah at least once, and 64 students (22.6%) were classified as frequent hookah smokers. Only 15 (4.7%) reported a health care provider asking about hookah during visits, whereas 36 (12.7%) admitted their hookah use to a health care provider. Conclusion: Hookah use was found to be highly prevalent among students in one urban university. This study supports the hypothesis that few health care providers broach the topic with patients. Additional research on health consequences of hookah use, education, and improved screening is warranted.     

Joint modelling of longitudinal response and time-to-event data using conditional distributions: a Bayesian perspective

Over the last 20 or more years a lot of clinical applications and methodological development in the area of joint models of longitudinal and time-to-event outcomes have come up. In these studies, patients are followed until an event, such as death, occurs. In most of the work, using subject-specific random-effects as frailty, the dependency of these two processes has been established. In this article, we propose a new joint model that consists of a linear mixed-effects model for longitudinal data and an accelerated failure time model for the time-to-event data. These two sub-models are linked via a latent random process. This model will capture the dependency of the time-to-event on the longitudinal measurements more directly. Using standard priors, a Bayesian method has been developed for estimation. All computations are implemented using OpenBUGS. Our proposed method is evaluated by a simulation study, which compares the conditional model with a joint model with local independence by way of calibration. Data on Duchenne muscular dystrophy (DMD) syndrome and a set of data in AIDS patients have been analysed.     

Kinship institutions and sex ratios in India

This article explores the relationship between kinship institutions and sex ratios in India at the turn of the twentieth century. Because kinship rules vary by caste, language, religion, and region, we construct sex ratios by these categories at the district level by using data from the 1901 Census of India for Punjab (North), Bengal (East), and Madras (South). We find that the male-to-female sex ratio varied positively with caste rank, fell as one moved from the North to the East and then to the South, was higher for Hindus than for Muslims, and was higher for northern Indo-Aryan speakers than for the southern Dravidian-speaking people. We argue that these systematic patterns in the data are consistent with variations in the institution of family, kinship, and inheritance.