Inequalities in Transnational Families

Over the past two decades, interest in the transnational lifestyles of contemporary migrants has grown significantly. In this article, we focus not on transnational identities, processes or structures, but rather on the emergent literature on transnational families in the context of migration to the United States. Transnational family studies broadly fall into two thematic camps: 1) those that describe transnational households as cooperative units in the face of economic, political and legal constraint and 2) those that show how the conditions that lead family members to live apart exacerbate and create new sources of conflict within families. Whether highlighting family conflict or cooperation, contemporary transnational family studies differ theoretically from prior research on immigrant families. Instead of focusing on immigrant incorporation, this literature demonstrates how global structures of inequality at the macro-level affect the everyday lives of transnational family members, as well as how individual action reproduces or challenges these broader social inequalities.     

Potential Uncertainty Reduction in Model‐Averaged Benchmark Dose Estimates Informed by an Additional Dose Study

A methodology is presented for assessing the information value of an additional dosage experiment in existing bioassay studies. The analysis demonstrates the potential reduction in the uncertainty of toxicity metrics derived from expanded studies, providing insights for future studies. Bayesian methods are used to fit alternative dose‐response models using Markov chain Monte Carlo (MCMC) simulation for parameter estimation and Bayesian model averaging (BMA) is used to compare and combine the alternative models. BMA predictions for benchmark dose (BMD) are developed, with uncertainty in these predictions used to derive the lower bound BMDL. The MCMC and BMA results provide a basis for a subsequent Monte Carlo analysis that backcasts the dosage where an additional test group would have been most beneficial in reducing the uncertainty in the BMD prediction, along with the magnitude of the expected uncertainty reduction. Uncertainty reductions are measured in terms of reduced interval widths of predicted BMD values and increases in BMDL values that occur as a result of this reduced uncertainty. The methodology is illustrated using two existing data sets for TCDD carcinogenicity, fitted with two alternative dose‐response models (logistic and quantal‐linear). The example shows that an additional dose at a relatively high value would have been most effective for reducing the uncertainty in BMA BMD estimates, with predicted reductions in the widths of uncertainty intervals of approximately 30%, and expected increases in BMDL values of 5–10%. The results demonstrate that dose selection for studies that subsequently inform dose‐response models can benefit from consideration of how these models will be fit, combined, and interpreted.     

Predictive comparison of joint longitudinal-survival modeling: a case study illustrating competing approaches

The joint modeling of longitudinal and survival data has received extraordinary attention in the statistics literature recently, with models and methods becoming increasingly more complex. Most of these approaches pair a proportional hazards survival with longitudinal trajectory modeling through parametric or nonparametric specifications. In this paper we closely examine one data set previously analyzed using a two parameter parametric model for Mediterranean fruit fly (medfly) egg-laying trajectories paired with accelerated failure time and proportional hazards survival models. We consider parametric and nonparametric versions of these two models, as well as a proportional odds rate model paired with a wide variety of longitudinal trajectory assumptions reflecting the types of analyses seen in the literature. In addition to developing novel nonparametric Bayesian methods for joint models, we emphasize the importance of model selection from among joint and non joint models. The default in the literature is to omit at the outset non joint models from consideration. For the medfly data, a predictive diagnostic criterion suggests that both the choice of survival model and longitudinal assumptions can grossly affect model adequacy and prediction. Specifically for these data, the simple joint model used in by Tseng et al. (Biometrika 92:587–603, 2005) and models with much more flexibility in their longitudinal components are predictively outperformed by simpler analyses. This case study underscores the need for data analysts to compare on the basis of predictive performance different joint models and to include non joint models in the pool of candidates under consideration.     

Restroom restrictions: How race and sexuality have affected bathroom legislation

This research details how current bathroom legislation that discriminates against trans individuals is rooted in the same discriminatory practices that permitted Jim Crow bathroom policies to exist. Sexualities that are considered nonwhite, non‐heterosexual, or non‐cisgendered are considered “othered,” as they are perceived to be a threat to the fertility of cis white women. This study details how sexuality stereotypes have been defined between white and black men and women, homosexual people, and trans‐people (with an emphasis on trans women).     

Predicting psychological ripple effects: the role of cultural identity, in-group/out-group identification, and attributions of blame in crisis communication

Incidents of intentional food contamination can produce ripple effects in consumers such as reduced trust and increased anxiety. In their postcrisis communication, food companies often direct the blame at the perpetrator in an effort to mitigate potential losses and regain consumer trust. The attempt to placate consumers may, in itself, potentially create psychological ripple effects in message readers. This study examined the interacting influence of two message characteristics: identity of the perpetrator of the crime (in-group/out-group membership), and the attribution of blame (reason why the perpetrator committed the crime), with message receiver characteristic (cultural identity) on psychological ripple effects such as blame, trust, anxiety, and future purchase intention. Results indicated that although group membership of the perpetrator was not significant in predicting outcomes for the organization, the attribution communicated in the message was. American message receivers blamed the organization more and trusted it less when personal dispositional attributions were made about the perpetrator. Asian message receivers blamed the organization more and trusted it less when situational attributions were made about the perpetrator. Lowered trust in the company and increased anxiety correlated with lower purchase intent for both American and Asian message receivers. Implications for crisis message design are discussed.     

Minimum covering with travel cost

Given a polygon and a visibility range, the Myopic Watchman Problem with Discrete Vision (MWPDV) asks for a closed path P and a set of scan points $\mathcal{S}$ , such that (i) every point of the polygon is within visibility range of a scan point; and (ii) path length plus weighted sum of scan number along the tour is minimized. Alternatively, the bicriteria problem (ii??) aims at minimizing both scan number and tour length. We consider both lawn mowing (in which tour and scan points may leave?P) and milling (in which tour, scan points and visibility must stay within P) variants for the MWPDV; even for simple special cases, these problems are NP-hard. We show that this problem is NP-hard, even for the special cases of rectilinear polygons and L _?? scan range 1, and negligible small travel cost or negligible travel cost. For rectilinear MWPDV milling in grid polygons we present a 2.5-approximation with unit scan range; this holds for the bicriteria version, thus for any linear combination of travel cost and scan cost. For grid polygons and circular unit scan range, we describe a bicriteria 4-approximation. These results serve as stepping stones for the general case of circular scans with scan radius r and arbitrary polygons of feature size a, for which we extend the underlying ideas to a $\pi(\frac{r}{a}+\frac{r+1}{2})$ bicriteria approximation algorithm. Finally, we describe approximation schemes for MWPDV lawn mowing and milling of grid polygons, for fixed ratio between scan cost and travel cost.     

Estimation bias of different design and analytical strategies in dual-frame telephone surveys: an empirical evaluation

Dual-frame survey designs have become increasingly popular in large-scale telephone surveys. This is due to the lack of coverage of the traditional landline survey design and the escalating use of cell phones in recent years. Several estimation strategies have been proposed and their properties have been discussed under ideal scenarios, including pseudo-maximum-likelihood estimation, single-frame estimation, and simple composite estimation [C.J. Skinner and J.N.K. Rao, Estimation in dual frame surveys with complex designs, J. Am. Statist. Assoc. 91 (1996), pp. 349–356; S.L. Lohr and J.N.K. Rao, Inference from dual frame surveys, J. Am. Statist. Assoc. 95 (2000), pp. 271–280]. In practice, estimation in dual-frame telephone surveys is vulnerable to biases and errors (e.g. inaccessibility, topic/mode salience, and measurement error). The investigation of the performance of popular dual-frame estimation methods is scarce in real and less ideal scenarios. Through an innovatively designed simulation study, we compare the estimation bias under different sampling designs with various estimation strategies. To reduce bias, different raking strategies are compared. Simulated scenarios incorporating sampling costs are examined for practical considerations. Overall, the cell phone-only design yields results with the least bias and variance. When accurate covariate information is available for post-stratification, raking estimates from the cell phone-any design also perform very well. We also provide SAS macros for this simulation evaluation upon request. Survey practitioners can fine-tune the parameters based on their prior knowledge of the target population and run the simulation under different scenarios to gain more insights into how to optimally design and analyse telephone surveys.