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.     

The Robustness of Trend Stationarity: An Illustration with the Extended Nelson-Plosser Dataset

We re-evaluate Andreu and Spanos's findings in favour of trend stationarity by considering the extended Nelson-Plosser data set. This expanded (to 1988) data set includes a period of rather different behaviour compared with the original Nelson-Plosser data used by Andreou and Spanos. We find that Andreou and Spanos's models (with only minor adjustments) exhibit remarable stability over this extended period, and indicate that their conclusions are more robust than they have shown.     

How Welfare Policies Affect Adolescents' School Outcomes: A Synthesis of Evidence From Experimental Studies

Using data from 8 random assignment studies and employing meta‐analytic techniques, this article provides systematic evidence that welfare and work policies targeted at low‐income parents have small adverse effects on some school outcomes among adolescents ages 12 to 18 years at follow‐up. These adverse effects were observed mostly for school performance outcomes and occurred in programs that required mothers to work or participate in employment‐related activities and those that encouraged mothers to work voluntarily. The most pronounced negative effects on school outcomes occurred for the group of adolescents who had a younger sibling, possibly because of the increased home and sibling care responsibilities they assumed as their mothers increased their employment.     

Rural/Urban Differences in Child Growth and Survival in Bolivia

Abstract Using data from a national survey in Bolivia and from a regional sample of poor communities in two regions of Bolivia, we model the effects of community conditions, household characteristics, and social relations on child health as measured by child mortality and stunted growth. Based on national data, children in rural areas are twice as likely to die before the age of two than are children in large cities, and about one‐third of the children in rural areas are stunted. Including measures of community, household, and maternal characteristics accounts for at least two‐thirds of the urban/rural difference in child health. We conclude that expansion of health services, improvements in household and community sanitation, and socioeco‐nomic development are all needed to overcome the rural disadvantage in child health.     

Muted Masculinity as an Outsider Strategy: Gender Sharing in Ethnographic Work with Wives of Professional Athletes

Using findings from a study of the world of the wives of professional athletes, this article explores the complex motivations for and displays of trust, rapport, and group acceptance during ethnographic research. Episodic exchanges between a male ethnographer and female collaborators revealed subtle issues of gender and perceived relative worth. This article proposes the outsider strategy of “muted masculinity” as a means of exploring ethnographic issues in which the boundaries between insiders and outsiders are uncertain.     

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.     

A general inverse sampling scheme and its application to adaptive cluster sampling

Not having a variance estimator is a seriously weak point of a sampling design from a practical perspective. This paper provides unbiased variance estimators for several sampling designs based on inverse sampling, both with and without an adaptive component. It proposes a new design, which is called the general inverse sampling design, that avoids sampling an infeasibly large number of units. The paper provide estimators for this design as well as its adaptive modification. A simple artificial example is used to demonstrate the computations. The adaptive and non‐adaptive designs are compared using simulations based on real data sets. The results indicate that, for appropriate populations, the adaptive version can have a substantial variance reduction compared with the non‐adaptive version. Also, adaptive general inverse sampling with a limitation on the initial sample size has a greater variance reduction than without the limitation.     

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.     

Transnational Migration: Bringing Gender In

This article aims to bring gender into an even tighter transnational migration focus by broadening and deepening our original framework of “gendered geographies of power,” linking it more directly to existing and emerging scholarship. We examine and highlight previously neglected areas such as the role of the state and the social imaginary in gendering transnational processes and experiences. We identify topics that remain under‐appreciated, under‐researched, and/or under‐theorized. Finally, we initiate a discussion of how a gendered analysis of transnational migration can help bridge this particular research to other gendered transnational processes under study that do not privilege migration.