Migration Planning Among Female Prospective Labour Migrants from Nepal: A Comparison of First‐Time and Repeat‐Migrants

As international female labour migration has increased, so too have efforts to prevent the exploitation of labour migrants. However, evidence to underpin prevention efforts remains limited, with little known about labour migrants’ migration planning processes. Using data from a survey of female prospective labour migrants from Nepal, this article compares socio‐demographics and migration‐planning processes between first‐time and repeat‐migrants. We identified several factors which might increase repeat‐migrants’ vulnerability to exploitation during the migration process, or obstruct their engagement in pre‐migration interventions: more rapid migration planning than first‐time migrants; lower involvement in community groups; and a perception that they already have the knowledge they need. Only one‐third of repeat‐migrants planned to go to the same destination and 42 per cent to work in the same sector as previously. With repeat‐migration a common livelihoods strategy, it is crucial that interventions are guided by evidence on the needs of both first‐time‐ and repeat‐migrants.     

Computational Forecasting of Wavelet-converted Monthly Sunspot Numbers

Monthly average sunspot numbers follow irregular cycles with complex nonlinear dynamics. Statistical linear models constructed to forecast them are therefore inappropriate, while nonlinear models produce solutions sensitive to initial conditions. Two computational techniques - neural networks and genetic programming - that have their advantages are applied instead to the monthly numbers and their wavelet-transformed and wavelet-denoised series. The objective is to determine if modeling wavelet-conversions produces better forecasts than those from modeling series' observed values. Because sunspot numbers are indicators of geomagnetic activity their forecast is important. Geomagnetic storms endanger satellites and disrupt communications and power systems on Earth.     

Monte Carlo Approximations of the Quantiles of a Sample Statistic

We consider in this article the problem of numerically approximating the quantiles of a sample statistic for a given population, a problem of interest in many applications, such as bootstrap confidence intervals. The proposed Monte Carlo method can be routinely applied to handle complex problems that lack analytical results. Furthermore, the method yields estimates of the quantiles of a sample statistic of any sample size though Monte Carlo simulations for only two optimally selected sample sizes are needed. An analysis of the Monte Carlo design is performed to obtain the optimal choices of these two sample sizes and the number of simulated samples required for each sample size. Theoretical results are presented for the bias and variance of the numerical method proposed. The results developed are illustrated via simulation studies for the classical problem of estimating a bivariate linear structural relationship. It is seen that the size of the simulated samples used in the Monte Carlo method does not have to be very large and the method provides a better approximation to quantiles than those based on an asymptotic normal theory for skewed sampling distributions.     

句法角色与话题性对实体突显性的影响

句法角色与话题性都会影响语篇实体的突显性程度。采用汉语续写实验,将实验句置于语境之中,在句法角色恒定条件下操控话题性和指称形式等变量,可探察实体作为语篇话题和非话题在续写时的表征趋势,即重述形式。实验发现,在续写初期,话题性不能影响实体的重述,它与句法角色之间无交互作用|在续写后期,话题性确实对实体重述起到一定作用。此外,目标句给定指称形式虽然不影响实体重述,但在一定条件下会影响被试对重述形式的选择。     

Heteroscedastic Regression Models and Applications to Off-line Quality Control

We discuss in the present paper the analysis of heteroscedastic regression models and their applications to off-line quality control problems. It is well known that the method of pseudo-likelihood is usually preferred to full maximum likelihood since estimators of the parameters in the regression function obtained are more robust to misspecification of the variance function. Despite its popularity, however, existing theoretical results are difficult to apply and are of limited use in many applications. Using more recent results in estimating equations, we obtain an efficient algorithm for computing the pseudo-likelihood estimator with desirable convergence properties and also derive simple, explicit and easy to apply asymptotic results. These results are used to look in detail at variance minimization in off-line quality control, yielding techniques of inferences for the optimized design parameter. In application of some existing approaches to off-line quality control, such as the dual response methodology, rigorous statistical inference techniques are scarce and difficult to obtain. An example of off-line quality control is presented to discuss the practical aspects involved in the application of the results obtained and to address issues such as data transformation, model building and the optimization of design parameters. The analysis shows very encouraging results, and is seen to be able to unveil some important information not found in previous analyses.     

Estimation in the presence of incidental parameters

This paper considers the estimation of “structural” parameters when the number of unknown parameters increases with the sample size. Neyman and Scott (1948) had demonstrated that maximum likelihood estimators (MLE) of structural parameters may be inconsistent in this case. Patefield (1977) further observed that the asymptotic covariance matrix of the MLE is not equal to the inverse of the information matrix. In this paper we establish asymptotic properties of estimators (which include in particular the MLE) obtained via the usual likelihood approach when the incidental parameters are first replaced by their estimates (which are allowed to depend on the structural parameters). Conditions for consistency and asymptotic normality together with a proper formula for the asymptotic covariance matrix are given. The results are illustrated and applied to the problem of estimating linear functional relationships, and mild conditions on the incidental parameters for the MLE (or an adjusted MLE) to be consistent and asymptotically normal are obtained. These conditions are weaker than those imposed by previous authors.     

Polyhedral combinatorics of the cardinality constrained quadratic knapsack problem and the quadratic selective travelling salesman problem

This paper considers the Cardinality Constrained Quadratic Knapsack Problem (QKP) and the Quadratic Selective Travelling Salesman Problem (QSTSP). The QKP is a generalization of the Knapsack Problem and the QSTSP is a generalization of the Travelling Salesman Problem. Thus, both problems are NP hard. The QSTSP and the QKP can be solved using branch-and-cut methods. Good bounds can be obtained if strong constraints are used. Hence it is important to identify strong or even facet-defining constraints. This paper studies the polyhedral combinatorics of the QSTSP and the QKP, i.e. amongst others we identify facet-defining constraints for the QSTSP and the QKP, and provide mathematical proofs that they do indeed define facets. Author now works at Motorola. (2005 onwards)     

Parents’ Decision Making and Their Information Needs Concerning Treatments for Child Anxiety: Implications for Family-Centered Practice

Collaborative decision making is a central feature of family-centered practice and is important to families in treatment planning. This study explored parents’ preferences for decision making involvement and their information needs regarding treatment for child anxiety. Qualitative interviews conducted with 19 parents revealed four main themes: (1) parents regard themselves as protectors, (2) parents desire involvement in decision making, (3) information is key in decision making, and (4) not all treatments are perceived as equal. Parents reported a strong desire to maintain control over the final treatment decision. They preferred a wide range of information about treatment and the health-care provider. Implications for implementing family-centered practice are discussed.     

A network ridesharing experiment with sequential choice of transportation mode

Within the last decade, there has been a dramatic bloom in ridesharing businesses along with the emergence of new enabling technologies. A central issue in ridesharing, which is also important in the general domain of cost-sharing in economics and computer science, is that the sharing of cost implies positive externalities and hence coordination problems for the network users. We investigate these problems experimentally in the present study. In particular, we focus on how sequential observability of transportation mode choices can be a powerful facilitator of coordination in ridesharing. Our study abstracts the essential issues of coordination in ridesharing into a directed network game with experimentally testable predictions. In line with the theoretical analysis, our experimental evidence shows that even a limited extent of sequential choice observability might lead to efficient coordination. However, convergence to efficiency is slower with more limited observability, resulting in a significant increase in travel cost.     

The roles of caregivers and friends in adolescent daily emotion dynamics

Daily emotion dynamics provide valuable information about individuals’ emotion processes as they go about their lives. Emotion dynamics such as emotion levels (mean), emotion variability (degree of fluctuation), and emotion network density (strength of temporal connections among emotions) are associated with risks for various psychopathology in youth and adults. Prior work has shown that caregivers and friends play crucial socializing roles in adolescent emotional well-being, but less is known about their roles in daily emotion dynamics. This study examined whether caregiver emotion coaching, caregiver-adolescent closeness, and friendship quality were associated with adolescents’ emotion levels, emotion variability, and emotion network density. Further, we examined whether caregiver-adolescent closeness moderated the associations between coaching and emotion dynamics. Participants were 150 adolescents (61% girls; M_age = 14.75) and one of their caregivers (95% female; M_age = 43.35) who completed a baseline survey and 21 daily surveys. Results showed that caregiver emotion coaching interacted with caregiver-adolescent closeness in predicting emotion levels and variability. Specifically, when closeness was higher, emotion coaching was significantly associated with lower sadness and anger levels, higher happiness levels, and lower happiness variability. Caregiver emotion coaching, independent of closeness, was also associated with lower anxiety levels, lower sadness variability, and lower emotion network density. Friendship quality was significantly associated with lower levels of sadness, anxiety, and anger, higher levels of happiness, and lower variability in anxiety and anger. These findings suggest that caregivers and friends are central to everyday emotion levels and variability and a more flexible emotion system in adolescents.