Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

Culturalising the Abject: Islam,Law and Moral Panic in the West

This paper explores the construction of Islam as abject and the symbolic positioning of Muslims as being outside secular modernity in Australia through an analysis of the way the criminal legal process and perceptions of criminality are culturalised. The empirical focus is gang rape and the trials of Muslim youth on gang rape charges in Sydney between 2000–2003 which quickly became culturally inflected as ‘Muslim’ and ‘Lebanese’ by media reporting of the criminal trials and moral panic about them as source of social menace. Three dimensions of culturalisation of crime and the criminalisation of culture are identified in the criminal legal process and media reporting of it; firstly the cultural inflection of new laws against gang rape by their association with particular events and trials; secondly the introduction of ‘cultural defence’ by the accused as a mitigating factor in the criminal legal process; thirdly, media reporting and commentary on criminal cases which emphasize cultural explanations for individual criminal behaviour.     

Population constraints on pooled surveys in demographic hazard modeling

In non-experimental research, data on the same population process may be collected simultaneously by more than one instrument. For example, in the present application, two sample surveys and a population birth registration system all collect observations on first births by age and year, while the two surveys additionally collect information on women’s education. To make maximum use of the three data sources, the survey data are pooled and the population data introduced as constraints in a logistic regression equation. Reductions in standard errors about the age and birth-cohort parameters of the regression equation in the order of three-quarters are obtained by introducing the population data as constraints. A halving of the standard errors about the education parameters is achieved by pooling observations from the larger survey dataset with those from the smaller survey. The percentage reduction in the standard errors through imposing population constraints is independent of the total survey sample size.     

Causal inference with generalized structural mean models

Summary.  We estimate cause–effect relationships in empirical research where exposures are not completely controlled, as in observational studies or with patient non-compliance and self-selected treatment switches in randomized clinical trials. Additive and multiplicative structural mean models have proved useful for this but suffer from the classical limitations of linear and log-linear models when accommodating binary data. We propose the generalized structural mean model to overcome these limitations. This is a semiparametric two-stage model which extends the structural mean model to handle non-linear average exposure effects. The first-stage structural model describes the causal effect of received exposure by contrasting the means of observed and potential exposure-free outcomes in exposed subsets of the population. For identification of the structural parameters, a second stage 'nuisance' model is introduced. This takes the form of a classical association model for expected outcomes given observed exposure. Under the model, we derive estimating equations which yield consistent, asymptotically normal and efficient estimators of the structural effects. We examine their robustness to model misspecification and construct robust estimators in the absence of any exposure effect. The double-logistic structural mean model is developed in more detail to estimate the effect of observed exposure on the success of treatment in a randomized controlled blood pressure reduction trial with self-selected non-compliance.     

Family Cap and Nonmarital Fertility: The Racial Conditioning of Policy Effects

Using an experimental design, this research examines the effect of the nation's first family cap on the births, abortions, and contraception use of over 8,000 women receiving public assistance in New Jersey. The family cap denies additional cash benefits to children conceived while the mother is receiving public assistance. Our research shows that a targeted welfare benefit manipulation does influence fertility behavior; however, the effect is conditioned by race. We find that Black women in the experimental group have a 21% lower birth rate and a 32% higher abortion rate than Black women in the control group. We do not find a birth effect for Hispanic or White women. We discuss the policy implications of the effects of a segmented family cap.     

Boundary Spaces

While shows like The X-Files and 24 have merged conspiracy theories with popular science (fictions), some video games have been pushing the narrative even further. Electronic Art's Majestic game was released in July 2001 and quickly generated media buzz with its unusual multi-modal gameplay. Mixing phone calls, faxes, instant messaging, real and "fake' websites, and email, the game provides a fascinating case of an attempt at new directions for gaming communities. Through story, mode of playing, and use of technology, Majestic highlights the uncertain status of knowledge, community and self in a digital age; at the same time, it allows examination of alternative ways of understanding games' role and purpose in the larger culture. Drawing on intricate storylines involving government conspiracies, techno-bio warfare, murder and global terror, players were asked to solve mysteries in the hopes of preventing a devastating future of domination. Because the game drew in both actual and Majestic-owned/-designed websites, it constantly pushed those playing the game right to borders where simulation collides with " factuality'. Given the wide variety of "legitimate' conspiracy theory, alien encounters and alternative science web pages, users often could not distinguish when they were leaving the game's pages and venturing into " real' World Wide Web sites. Its further use of AOL's instant messenger system, in which gamers spoke not only to bots but to other players, pushed users to evaluate constantly both the status of those they were talking to and the information being provided. Additionally, the game required players to occupy unfamiliar subject positions, ones where agency was attenuated, and which subsequently generated a multi-layered sense of unease among players. This mix of authentic and staged information in conjunction with technologically mediated roles highlights what are often seen as phenomenon endemic to the Internet itself; that is, the destabilization of categories of knowing, relating, and being.     

Measuring Substance Abuse Treatment Need Among Adults in Florida: A Social Indicators Approach

Determining the size and demographiccharacteristics of substance abuse populationsis extremely important for implementing publicpolicies aimed at the control of substanceabuse. Such information not only assists in theallocation of limited treatment resources bythe state, but also in the monitoring ofsubstance abuse trends over time and in theevaluation of innovative policy initiatives. Inthis study, we develop three composite measuresof treatment need. We then use these measuresto estimate treatment need for alcohol abuseand for controlled substance abuse within eachof Florida's 67 counties. This study providesan important empirical component of communityplanning, quantifying and, to a limited degree,specifying the level of need for the substanceabuse treatment of community residents. Anadditional benefit is the development of a costeffective and unobtrusive methodology fordetermining empirically when levels of need arechanging so that treatment levels can beadjusted accordingly. With proper use,policymakers can readily employ the methodologydeveloped in this study in Florida andelsewhere to make better-informed decisions inthe allocation of finite substance abusetreatment resources.     

Farming Patterns,Rural Restructuring,and Poverty: A Comparative Regional Analysis1

Abstract This study examines the contentions of two recent perspectives on rural economic organization and their implications for poverty. Building from (1) agrarian political economy and (2) the rural restructuring literatures, we present a comparative regional analysis of how farming patterns and other aspects of economic organization differentially affect poverty in rural areas. Data are based on 2,349 nonmetropolitan U.S. counties for the 1970–1980 period. Nonhired labor-dependent, family-operated farming (smaller and larger family farming) has relatively similar cross-regional effects on rural poverty. The effects of industrialized farming are more spatially variant, suggesting that this type of farming is integrated into regional political economies in different ways than are simple commodity units. However, farming patterns have only a small effect on rural poverty relative to other factors, such as the local employment structure, characteristics of the population, and geographic location. The results of this study highlight the need to move beyond the farm sector to understand both the dynamics of this sector and the socioeconomic consequences of rural restructuring. More broadly, the study underscores the importance of testing general sociological relationships under different spatial (e.g., regional) contexts.