Simulating the average run length for cusum schemes using variance reduction techniques

Some variance reduction techniques utilizing the total hazard are developed to estimate the average run lengths of the cumulative sum charts through simulation when the process follows a general probability distribution. Particularly, we propose the hazard estimator and the cycle estimator. Simulation results are shown for the exponential case and these estimators are compared with the raw simulation estimator. Applicability to multivariate CUSUM schemes is briefly discussed in the conclusion.     

ON BALANCE AND SYNERGY: FAMILY THERAPY AND QUALITATIVE RESEARCH REVISITED

Our respondents have provided though-provoking counterpoints to our original paper (Moon, Dillon, & Sprenkle, 1990). Our response is one of synthesis. First, we describe a continuum of social science inquiry paradigms as a framework for exploring the assumptions underlying our respective positions. Second, we address the key issues raised by our respondents. Third, we encourage balance in our research efforts and continuing dialogue. Finally we restate our basic thesis-that qualitative research methodology has the potential to advance the science and practice of family therapy.     

FAMILY THERAPY AND QUALITATIVE RESEARCH*

Qualitative research is becoming accepted by the scientific community as a viable way to explore and understand socialscience phenomena. The purpose of this paper is to describe the essential features of the qualitative research paradigm and to encourage further development of that paradigm in the field of family therapy. First, typical characteristics of qualitative research designs are delineated; these characteristics are illustrated with two extended examples from the qualitative research literature in the field of education. Next, possible applications of the qualitative paradigm to research issues in the field of family therapy are discussed. Finally, potential pitfalls that could inhibit the development of qualitative family therapy research are examined. It is hoped that this paper will serve as a stimulus for the development of qualititative research in the field of family therapy.     

A Spatiotemporal Model for Pollutant Concentrations

ABSTRACT

Contamination of underground water tables can be characterized by measurements that are mixtures of short-term spiking, long-term decline, and steady-state variations in contaminant levels. Classical statistical models often fail to capture the changes in contaminant flow because they rely on fitting smooth spatial and temporal functions across the region, smooth functions that might not comprehensively characterize contaminant change. In this article, a more comprehensive approach is presented for modeling such processes. This approach uses a new class of spatiotemporal models that can characterize a broad range of environmental processes. It also effectively uses Bayesian hierarchical model fitting and a novel use of near neighbors to model contamination in an underground water table.     

Permutation Methods for Comparing the Accuracy of Nested Prediction Models in Survival Analysis

When making patient-specific prediction, it is important to compare prediction models to evaluate the gain in prediction accuracy for including additional covariates. We propose two statistical testing methods, the complete data permutation (CDP) and the permutation cross-validation (PCV) for comparing prediction models. We simulate clinical trial settings extensively and show that both methods are robust and achieve almost correct test sizes; the methods have comparable power in moderate to large sample situations, while the CDP is more efficient in computation. The methods are also applied to ovarian cancer clinical trial data.     

GMM Estimation of Autoregressive Roots Near Unity with Panel Data

This paper investigates a generalized method of moments (GMM) approach to the estimation of autoregressive roots near unity with panel data and incidental deterministic trends. Such models arise in empirical econometric studies of firm size and in dynamic panel data modeling with weak instruments. The two moment conditions in the GMM approach are obtained by constructing bias corrections to the score functions under OLS and GLS detrending, respectively. It is shown that the moment condition under GLS detrending corresponds to taking the projected score on the Bhattacharya basis, linking the approach to recent work on projected score methods for models with infinite numbers of nuisance parameters (Waterman and Lindsay (1998)). Assuming that the localizing parameter takes a nonpositive value, we establish consistency of the GMM estimator and find its limiting distribution. A notable new finding is that the GMM estimator has convergence rate , slower than , when the true localizing parameter is zero (i.e., when there is a panel unit root) and the deterministic trends in the panel are linear. These results, which rely on boundary point asymptotics, point to the continued difficulty of distinguishing unit roots from local alternatives, even when there is an infinity of additional data.     

The influence of ideational contests of social policy on government welfare efforts

There has been limited empirical research on the interaction between media influence and governments' decision-making in the social policy field. Drawing on a wider study of the ideation of poverty in South Korea, this research tests if policy ideas represented in the media have bottom-up framing effects on policymaking and can be a reliable indicator of the government's social policy efforts. This study analysed the editorials of major Korean daily newspapers, over the period of a decade from 2000 to 2009. The analysis outcomes identified a significant correlation between the extent of poverty discussions in the media and government welfare spending.