Infant Affect During Parent—Infant Interaction at 3 and 6 Months: Differences Between Mothers and Fathers and Influence of Parent History of Depression

Fifty families participated in mother‐infant and father‐infant still‐face interaction at infant ages 3 and 6 months as part of a study of affect in early parent‐infant relationships. Infants' positive and negative affect and parents' positive affect and physical play were coded from videotapes. Consistent with previous research, during the normal condition, mothers displayed more positive affect than did fathers, and fathers were more likely than mothers to display physical play. Infants were more positive with mothers than with fathers. Parents' positive affect but not parent gender predicted infants' positive affect at 6 months. During the still‐face condition, infants of parents with a lifetime history of depression were more likely to display negative affect and less likely to display positive affect than infants with no such parent history. Infants' affect was unrelated to parents' current level of depressive symptoms, which indicates the value of considering family history of psychopathology when examining individual differences in infants' affect.     

Skewness and mixtures of normal distributions

The effect of skewness on hypothesis tests for the existence of a mixture of univariate and bivariate normal distributions is examined through a Monte Carlo study. A likelihood ratio test based on results of the simultaneous estimation of skewness parameters, derived from power transformations, with mixture parameters is proposed. This procedure detects the difference between inherent distributional skewness and the apparent skewness which is a manifestation of the mixture of several distributions. The properties of this test are explored through a simulation study.     

Optimal collection of information by partially informed agents

Abstract

In this paper we discuss different aspects of long memory behavior and applicable parametric models. We discuss the confusion that can arise when the empirical autocorrelation function decreases in a hyperbolic way.     

The Newsvendor Model with Consumer Search Costs

We study the newsvendor problem when consumers are heterogeneous either in their valuations of the newsvendor's product, in their valuations of an outside option available to them, or in both valuations. In this context, we observe that the outside option, which represents the value that a given consumer associates with choosing not to purchase the newsvendor's product, may be interpreted as a search cost. Taking into consideration whether consumers' valuations differ on either one dimension of heterogeneity or on both dimensions, we develop a framework for classifying newsvendor models that incorporate demand‐management effects. In particular, we show that this framework includes both the newsvendor model with price‐dependent demand and the newsvendor model with endogenous demand as special cases. In addition to making a conceptual contribution by developing and drawing insights from this framework, we make technical contributions by providing more general sufficient conditions under which the underlying optimization problems are well behaved.     

Using Audio Computer-Assisted Self-Interviewing and Interactive Voice Response to Measure Elder Mistreatment in Older Adults: Feasibility and Effects on Prevalence Estimates

Demographic trends indicate an aging population, highlighting the importance of collecting valid survey data from older adults. One potential issue when surveying older adults is use of technology to collect data on sensitive topics. Survey technologies like A-CASI and IVR have not been used with older adults to measure elder mistreatment. We surveyed 903 adults age 60 and older in Allegheny County, Pennsylvania (U.S.) with random assignment to one of four survey modes: (1) CAPI, (2) A-CASI, (3) CATI; and (4) IVR. We assessed financial, psychological, and physical mistreatment, and examined feasibility of A-CASI and IVR, and effects on prevalence estimates relative to CAPI and CATI. Approximately 83% of elders randomized to A-CASI/IVR used each technology, although 28% of respondents in the A-CASI condition refused to use headphones and read the questions instead. A-CASI produced higher six month prevalence rates of financial and psychological mistreatment than CAPI. IVR produced higher six month prevalence rates of psychological mistreatment than CATI. We conclude that, while IVR may be useful, A-CASI offers a more promising approach to the measurement of elder mistreatment.     

Pediatric Emergency Department Visits for Mental Health Crisis: Prevalence of Cyber-Bullying in Suicidal Youth

The objective of this work is to (1) study the prevalence of cyber-bullying amongst adolescents referred by Pediatric Emergency Department (PED) for urgent psychiatric assessment and (2) to examine the association between cyber-bullying and suicidal behavior to assist emergency department professionals in screening for risk and triage. This is a retrospective study of patients referred by PED to an urgent psychiatric clinic. Data was extracted for those with bullying victimization. Clinical variables included demographics, reason for referral, type of bullying, substance use, abuse, past psychiatric history, diagnosis and outcome. The cyber-bullying group was compared to those with traditional bullying and a group with no-bullying. Data analysis was conducted using Chi squares, multinomial and bimodal logistic regression. The urgent psychiatric clinic assessed 805 patients in 24 months, the prevalence of bullying was 26.9 % (n = 217). The prevalence of Cyber-bullying was 13.5 % (n = 109) and traditional bullying was 13.4 % (n = 108). Cyber-bullying victims have more suicidal ideation (χ² = 7.82, p = .005; 85.3  vs. 69.4 %), more sexual abuse (χ² = 5.75, p = .02; 29.4  vs. 15.7 %), more emotional abuse (χ² = 10.8, p = .01; 30.3  vs. 12.0 %) and physical abuse (χ² = 6.13, p = .01; 27.5  vs. 13.9 %) and a higher inpatient admission rate. Suicidal ideation is the presenting problem in more than two-thirds of patients, especially females, with history of cyber-bullying who present to the PED. Screening questions about cyber-bullying could assist emergency room professionals in establishing risk and making triage decisions.     

From Separate Corners to Dialogue and Action

How can higher education programs engage students in building a shared commons to address inequalities and foster commitment to intergroup collaboration? Intergroup dialogue is one such possibility to provide forums for meaningful engagement among students from diverse backgrounds. Findings from field experiments at nine colleges and universities show that students in intergroup dialogues increased significantly more than counterparts in control groups and social science comparison groups in their critiques of inequality and their commitments to post-college action to redress inequalities. Further, students in intergroup dialogues rated the frequency of the core communication processes more highly than the social science comparison students. The communication processes help account for the greater increase in students’ critiques of inequality and commitment to post-college actions.     

Particle Learning for Fat-Tailed Distributions

It is well known that parameter estimates and forecasts are sensitive to assumptions about the tail behavior of the error distribution. In this article, we develop an approach to sequential inference that also simultaneously estimates the tail of the accompanying error distribution. Our simulation-based approach models errors with a t_ν-distribution and, as new data arrives, we sequentially compute the marginal posterior distribution of the tail thickness. Our method naturally incorporates fat-tailed error distributions and can be extended to other data features such as stochastic volatility. We show that the sequential Bayes factor provides an optimal test of fat-tails versus normality. We provide an empirical and theoretical analysis of the rate of learning of tail thickness under a default Jeffreys prior. We illustrate our sequential methodology on the British pound/U.S. dollar daily exchange rate data and on data from the 2008–2009 credit crisis using daily S&P500 returns. Our method naturally extends to multivariate and dynamic panel data.