Effects of a single outlier on arma identification

Fox (1972), Box and Tiao (1975), and Abraham and Box (1979) have proposed methods for detecting outliers in time series whose ARMA form is known (or identified). We show that the existence of a single aberrant observation, innovation, or intervention causes an ARMA model to be misidentified using unadjusted autocorrelation (acf) and partial autocorrelation estimates. The magnitude, location, type of outlier, and in some cases the ARMA's parameters, affect the identification outcome. We use variance inflation, signal-to-noise ratios, and acf critical values to determine an ARMA model's susceptibility to misidentifi-cation. Numerical and simulation examples suggest how to iteratively use the outlier detection methods in practice.     

On the Streets,Under Arrest: Policing Homelessness in the 21st Century

Since the earliest days of the discipline, sociologists have viewed homelessness as a premier index of inequality and poverty more generally. Sociologists have increasingly turned to the regulation and policing of homelessness as a lens for analyzing how a given society understands and interacts with those who exist at the bottom of the social hierarchy. Against this intellectual backdrop, this article traces recent developments in the policing of homelessness, as well as the corresponding academic attempts to make sense of this empirical phenomenon. Doing so demonstrates that a vast majority of analyses have focused narrowly on the punitive and exclusionary functions of policing and, as a result, have tended to overlook issues surrounding differentiated functions, organizational dynamics, spatial contingencies, and questions of agency. This article complicates existing approaches and thereby lays the foundation for a more accurate and nuanced rendering of the policing of homelessness.     

Examining links between cocaine use and street-based sex work in New South Wales, Australia

We examined potential links between cocaine use and street-based sex work in New South Wales (NSW), Australia, following reports of increased cocaine use among injection drug users (IDU). Police data on prostitution and possession/use of cocaine was analysed using time series analysis. Interviews with key informants and IDU were also conducted, and data on cocaine use from ongoing monitoring systems targeted at IDU were analysed. There was a clear increase in cocaine use among IDU which occurred in 2001. This occurred at the same time as an increase in prostitution offenses. Qualitative data suggested that a greater number of primary heroin users were engaging in street-based sex work, which was driven in part by the increases in cocaine use among this group. Subsequent reductions in cocaine availability led to decreased cocaine use and possession offenses, along with reductions in prostitution offenses.     

Variance estimation in complex survey sampling for generalized linear models

Summary.  Complex survey sampling is often used to sample a fraction of a large finite population. In general, the survey is conducted so that each unit (e.g. subject) in the sample has a different probability of being selected into the sample. For generalizability of the sample to the population, both the design and the probability of being selected into the sample must be incorporated in the analysis. In this paper we focus on non-standard regression models for complex survey data. In our motivating example, which is based on data from the Medical Expenditure Panel Survey, the outcome variable is the subject's 'total health care expenditures in the year 2002'. Previous analyses of medical cost data suggest that the variance is approximately equal to the mean raised to the power of 1.5, which is a non-standard variance function. Currently, the regression parameters for this model cannot be easily estimated in standard statistical software packages. We propose a simple two-step method to obtain consistent regression parameter and variance estimates; the method proposed can be implemented within any standard sample survey package. The approach is applicable to complex sample surveys with any number of stages.     

The Ethical Dilemma of Ethical Committees

The Nuremberg code, a response to the 1946 Nuremberg Medical Trials, was the first attempt to formally state ethical requirements for medical research. The Code was generally ignored as a response to the peculiarly barbaric Nazi atrocities and an unnecessary fetter on normal research. A series of research scandals, however, led to more successful attempts at regulating medical research and to the introduction of various ethical committees during the 1970s. Since then, ethical committees have expanded their remit to regulate social as well as medical research and operate according to precautionary standards that far exceed what is necessary to protect public safety. Ethical committees block investigations of medical practice even when the intent is to benefit patients directly and they prevent social research entailing even far‐fetched possibilities of ‘stress’. Although purportedly designed to protect patients and civil liberties, modern ethical regulation damages the doctor–patient relationship, undermines professional responsibility, and encourages negative scientific practice.     

Using auxiliary data for parameter estimation with non-ignorably missing outcomes

We propose a method for estimating parameters in generalized linear models when the outcome variable is missing for some subjects and the missing data mechanism is non-ignorable. We assume throughout that the covariates are fully observed. One possible method for estimating the parameters is maximum likelihood with a non-ignorable missing data model. However, caution must be used when fitting non-ignorable missing data models because certain parameters may be inestimable for some models. Instead of fitting a non-ignorable model, we propose the use of auxiliary information in a likelihood approach to reduce the bias, without having to specify a non-ignorable model. The method is applied to a mental health study.