Efficient heterogeneous sampling for stochastic simulation with an illustration in health care applications

In modeling disease transmission, contacts are assumed to have different infection rates. A proper simulation must model the heterogeneity in the transmission rates. In this article, we present a computationally efficient algorithm that can be applied to a population with heterogeneous transmission rates. We conducted a simulation study to show that the algorithm is more efficient than other algorithms for sampling the disease transmission in a subset of the heterogeneous population. We use a valid stochastic model of pandemic influenza to illustrate the algorithm and to estimate the overall infection attack rates of influenza A (H1N1) in a Canadian city.     

同意观念的历史谱系与当代困境

通过提出明示同意与默示同意这两个不同的同意概念并强调有别于集体同意之个体同意的重要性，特别是通过对默示同意的分析和说明，洛克使得近代意义上的同意理论逐渐浮出水面。同意理论在颠覆君权神授理论、确认人民主权思想的过程中有着无可置疑的历史价值。虽然在现当代，同意理论因遭遇到越来越多的诟病而逐渐步入困境，但同意理论并非一无是处。对于当代中国社会来说，强调政府及政府行为必须经过人民的同意这一点，对于政治体制的改革以及政治秩序的合法构建来说仍然具有极为重要且深远的意义。     

Popularity Contagion Among Adolescents

This study aimed to support the theory of popularity contagion, which posits that popularity spreads among friends spontaneously and regardless of behavioral changes. Peer nominations of status and behavior were collected annually between 6th and 12th grades from a total of 1062 adolescents. Longitudinal hypotheses were mostly supported using path analyses, showing (1) that individual popularity could be predicted by friends’ popularity levels over time, even when controlling for stability of individual popularity; (2) that this prediction was not accounted for by behavioral contagion of aggressive or prosocial behaviors; and (3) that individual social preference generally could not be predicted by friends’ preference levels over time. Implications, limitations, and directions for future research are discussed.     

Assessing the Need for Higher Levels of Care Among Problem Gambling Outpatients

Most treatment for gambling disorder is provided on an outpatient basis. Only a small number of jurisdictions in North America provide higher levels of gambling treatment, such as residential or intensive outpatient (IOP) care, despite the potential need for these services. Further, there appear to be few guidelines for determining appropriate level of gambling treatment. The aim of the present study was to assess the appropriateness of higher levels of problem gambling care among clients receiving outpatient treatment. Problem gamblers and their therapists independently completed questionnaires that assessed the need and desire for residential and IOP treatment. About 42% of problem gambling outpatients noted that they would be “probably” or “definitely” willing to attend residential treatment, and about half indicated they would be equally likely to attend IOP. Therapists recommended about a third of their clients as appropriate for higher levels of care. For both client and therapist assessments, there was a significant association between desire or recommendation for level of treatment and severity of gambling and co-occurring problems. Further, therapist recommendations for level of care were significantly associated with client willingness to attend higher levels of treatment. Our data reveal the potential need for higher levels of care for problem gambling, as evaluated by clients and their therapists. Policy implications for the funding of residential and IOP treatment are discussed.     

Heterogeneous climate effects on human migration in Indonesia

We examine the effect of anomalous temperatures, rainfall levels, and monsoon timing on migration outcomes in Indonesia. Using panel data from the Indonesian Family Life Survey and high-resolution climate data, we assess whether intra- and inter-province moves are used as a response to climatic shocks. We evaluate the relative importance of temperature, rainfall, and monsoon timing for migration. Only temperature and monsoon timing have significant effects, and these do not operate in the direction commonly assumed. Estimated effects vary according to individuals’ gender, membership in a farm household, and location. We also analyze climate effects on sources of household income, which highlights the multi-phasic nature of household responses. Results undermine narratives of a uniform global migratory response to climate change and highlight the heterogeneous use of migration as a response to such changes. By extending previous research on environmentally induced migration in Indonesia, we also highlight the sensitivity of estimates to alternative climate and migration measures.     

Latent Profiles of Discrimination and Socialization Predicting Ethnic Identity and Well‐Being Among Asian American Adolescents

Ethnic identity is rooted in sociocultural processes, but little is known about how social interactions predict its longitudinal changes. Using data from 154 Asian American adolescents, latent profile analysis derived four typologies based on unfair treatment (i.e., discrimination, model minority stereotyping) and ethnic socialization (i.e., cultural socialization, preparation for bias, promotion of mistrust): Low Cultural Salience, High Cultural Salience with Marginalization, Culturally Prepared with Low Mistrust, and High Mistrust/Discrimination. Few gender or generational differences in profile membership were found. Positive outcomes were linked to adolescents attuned to both positive and negative experiences, Culturally Prepared with Low Mistrust, who reported increases in ethnic belonging and decreases in negative emotions. The implications for identity formation and adjustment are discussed.     

Hierarchical likelihood approach to non-Gaussian factor analysis

Factor models, structural equation models (SEMs) and random-effect models share the common feature that they assume latent or unobserved random variables. Factor models and SEMs allow well developed procedures for a rich class of covariance models with many parameters, while random-effect models allow well developed procedures for non-normal models including heavy-tailed distributions for responses and random effects. In this paper, we show how these two developments can be combined to result in an extremely rich class of models, which can be beneficial to both areas. A new fitting procedures for binary factor models and a robust estimation approach for continuous factor models are proposed.     

Young Adult and Parent Perceptions of Facilitation: Associations with Overparenting,Family Functioning,and Student Adjustment

Overparenting occurs when parents engage in developmentally inappropriate involvement in their children’s lives. This topic is salient in the context of young adults attending college, as this developmental stage necessitates independent decision-making and adjustment on the part of these students. At the same time, the turbulence involved in this transition might engender parental interference and facilitation that could impact young adults’ adjustment and perceived family functioning. This study used structural equation modeling to examine overparenting, perceived interference, facilitation, student adjustment, and family functioning in 302 parent–young adult dyads. Results indicated that overparenting was associated with facilitation, but not interference. Whereas this association was negative for young adults, it was positive for parents. This pattern was also reflected in the indirect effects of overparenting on student adjustment through young adults’ versus parents’ perceived facilitation. Young adults appear to have better outcomes when they perceive their parents to be facilitating their goals.     

A new algorithm for clustering based on kernel density estimation

In this paper, we present an algorithm for clustering based on univariate kernel density estimation, named ClusterKDE. It consists of an iterative procedure that in each step a new cluster is obtained by minimizing a smooth kernel function. Although in our applications we have used the univariate Gaussian kernel, any smooth kernel function can be used. The proposed algorithm has the advantage of not requiring a priori the number of cluster. Furthermore, the ClusterKDE algorithm is very simple, easy to implement, well-defined and stops in a finite number of steps, namely, it always converges independently of the initial point. We also illustrate our findings by numerical experiments which are obtained when our algorithm is implemented in the software Matlab and applied to practical applications. The results indicate that the ClusterKDE algorithm is competitive and fast when compared with the well-known Clusterdata and K-means algorithms, used by Matlab to clustering data.