Predicting infectious disease outbreak risk via migratory waterfowl vectors

The spread of an emerging infectious disease is a major public health threat. Given the uncertainties associated with vector-borne diseases, in terms of vector dynamics and disease transmission, it is critical to develop statistical models that address how and when such an infectious disease could spread throughout a region such as the USA. This paper considers a spatio-temporal statistical model for how an infectious disease could be carried into the USA by migratory waterfowl vectors during their seasonal migration and, ultimately, the risk of transmission of such a disease to domestic fowl. Modeling spatio-temporal data of this type is inherently difficult given the uncertainty associated with observations, complexity of the dynamics, high dimensionality of the underlying process, and the presence of excessive zeros. In particular, the spatio-temporal dynamics of the waterfowl migration are developed by way of a two-tiered functional temporal and spatial dimension reduction procedure that captures spatial and seasonal trends, as well as regional dynamics. Furthermore, the model relates the migration to a population of poultry farms that are known to be susceptible to such diseases, and is one of the possible avenues toward transmission to domestic poultry and humans. The result is a predictive distribution of those counties containing poultry farms that are at the greatest risk of having the infectious disease infiltrate their flocks assuming that the migratory population was infected. The model naturally fits into the hierarchical Bayesian framework.     

Bootstrap Testing of Hypotheses on Co‐Integration Relations in Vector Autoregressive Models

It is well known that the finite‐sample properties of tests of hypotheses on the co‐integrating vectors in vector autoregressive models can be quite poor, and that current solutions based on Bartlett‐type corrections or bootstrap based on unrestricted parameter estimators are unsatisfactory, in particular in those cases where also asymptotic χ² tests fail most severely. In this paper, we solve this inference problem by showing the novel result that a bootstrap test where the null hypothesis is imposed on the bootstrap sample is asymptotically valid. That is, not only does it have asymptotically correct size, but, in contrast to what is claimed in existing literature, it is consistent under the alternative. Compared to the theory for bootstrap tests on the co‐integration rank (Cavaliere, Rahbek, and Taylor, 2012), establishing the validity of the bootstrap in the framework of hypotheses on the co‐integrating vectors requires new theoretical developments, including the introduction of multivariate Ornstein–Uhlenbeck processes with random (reduced rank) drift parameters. Finally, as documented by Monte Carlo simulations, the bootstrap test outperforms existing methods.     

Bounding Optimal Expected Revenues for Assortment Optimization under Mixtures of Multinomial Logits

We consider assortment problems under a mixture of multinomial logit models. There is a fixed revenue associated with each product. There are multiple customer types. Customers of different types choose according to different multinomial logit models whose parameters depend on the type of the customer. The goal is to find a set of products to offer so as to maximize the expected revenue obtained over all customer types. This assortment problem under the multinomial logit model with multiple customer types is NP‐complete. Although there are heuristics to find good assortments, it is difficult to verify the optimality gap of the heuristics. In this study, motivated by the difficulty of finding optimal solutions and verifying the optimality gap of heuristics, we develop an approach to construct an upper bound on the optimal expected revenue. Our approach can quickly provide upper bounds and these upper bounds can be quite tight. In our computational experiments, over a large set of randomly generated problem instances, the upper bounds provided by our approach deviate from the optimal expected revenues by 0.15% on average and by less than one percent in the worst case. By using our upper bounds, we are able to verify the optimality gaps of a greedy heuristic accurately, even when optimal solutions are not available.     

Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Psychometric growth curve modeling techniques are used to describe a person’s latent ability and how that ability changes over time based on a specific measurement instrument. However, the same instrument cannot always be used over a period of time to measure that latent ability. This is often the case when measuring traits longitudinally in children. Reasons may be that over time some measurement tools that were difficult for young children become too easy as they age resulting in floor effects or ceiling effects or both. We propose a Bayesian hierarchical model for such a scenario. Within the Bayesian model we combine information from multiple instruments used at different age ranges and having different scoring schemes to examine growth in latent ability over time. The model includes between-subject variance and within-subject variance and does not require linking item specific difficulty between the measurement tools. The model’s utility is demonstrated on a study of language ability in children from ages one to ten who are hard of hearing where measurement tool specific growth and subject-specific growth are shown in addition to a group level latent growth curve comparing the hard of hearing children to children with normal hearing.KEYWORDS: Bayesian hierarchical models, psychometric modeling, language ability, growth curve modeling, longitudinal analysis     

Do the Constructs of the FACES IV Change Based on Definitions of “Family?” A Measurement Invariance Test

The Family Adaptability and Cohesion Scale (FACES) IV does not provide instructions about which family members respondents should think about while answering questions. This study examined which family members respondents thought about while completing the FACES IV, and if this changed measurement invariance and population heterogeneity of the measure. Using a sample of n = 511 individuals, a latent class analysis showed three distinct classes: Nuclear Family, Family of Origin, and All of the Above. The FACES IV demonstrated measurement invariance across classes on the majority of subscales; however, population heterogeneity tests suggested that the means and variances of the subscales varied across classes. The findings suggest further examination of how the measure functions with unique family constellations is warranted.     

The Politics of Women's Economic Independence

We identify the political conditions that shape the economicposition of married/cohabiting women and of the economicallymost vulnerable group of women—single mothers. Specifically,we examine the determinants of reductions in single mothers'poverty rate due to taxes and transfers, and women's wages relativeto spouses'/ partners' wages. The Luxembourg Income Study archiveyields an unbalanced panel with 71 observations on 15 countries.The principal determinants of poverty reduction due to taxesand transfers are left government, constitutional veto points,and welfare generosity. The relative wage of women in couplesis a function mainly of female labor force participation, parttime work among women, and women's mobilization. In explainingthe causal pathways to these outcomes, we highlight the interrelationshipsof welfare state, care, and labor market policies.     

12‐Month‐Olds Produce Others' Intended but Unfulfilled Acts

Following Meltzoff's (1995) behavioral reenactment paradigm, this study investigated the ability of 12‐month‐olds (N = 44) to reproduce a model's attempted‐but‐failed actions on objects. Testing was conducted using a novel set of objects designed to enable young infants to readily identify the potential outcome of the model's actions. Infants who saw an adult's attempted‐but‐failed actions now produced her intended outcomes at an equivalent rate to infants who saw the model's completed acts, and significantly more so than infants who either observed an adult manipulating the test apparatus using nontarget actions or who did not see any actions demonstrated on the test apparatus. This result shows that, contrary to previous studies, 12‐month‐olds can produce the intended but unconsummated acts of others.     

Negative (But Not Positive) Parenting Interacts with Infant Negative Affect to Predict Infant Approach: Evidence of Diathesis‐Stress

Temperament by parenting interactions may reflect that individuals with greater risk are more likely to experience negative outcomes in adverse contexts (diathesis‐stress) or that these individuals are more susceptible to contextual influences in a “for better or for worse” pattern (differential susceptibility). Although such interactions have been identified for a variety of child outcomes, prior research has not examined approach characteristics—excitement and approach toward pleasurable activities—in the first year of life. Therefore, this study investigated whether 6‐month maternal reported infant negative affect—a phenotypic marker of risk/susceptibility—interacted with 8‐month observed parenting behaviors (positive parenting, negative parenting) to predict 12‐month infant behavioral approach. Based on a sample of mothers and their infants (N = 150), results indicated that negative parenting was inversely associated with subsequent approach for infants with high, but not low, levels of negative affect. Similar results did not occur regarding positive parenting. These findings better fit a diathesis‐stress model rather than a differential susceptibility model. Implications and limitations of these findings are discussed.