The effect of natural disasters on nuptiality: evidence from L’Aquila earthquake (Italy)

Population and Environment - Drawing on socio-psychology and economics literature contributions, this paper provides an original conceptual framework examining whether and how natural disasters...     

Differences between matched heterosexual and non-heterosexual college students on defense mechanisms and psychopathological symptoms

Differences between heterosexual and non-heterosexual college students on measures of defense mechanisms and psychopathological symptoms were examined. Fifty-six (28 heterosexual, 28 non-heterosexual) subjects were drawn from a larger study of college student adjustment. Non-heterosexual subjects were matched to a heterosexual peer on several demographic variables as well as on attachment security/insecurity. Differences between the two groups on the Defense Mechanism Inventory and the Brief Symptom Inventory were tested. Contrary to traditional psychoanalytic conceptions of homosexuality, no differences were found between the two groups on any subscale of the Defense Mechanism Inventory, thereby repudiating one important aspect of traditional psychoanalytic theories on the development of homosexuality. Non-heterosexual students reported significantly higher levels of anxiety, depression, somaticization, paranoid ideation, general symptom severity, and suicidal ideation. These students appear to be at increased risk for psychopathology and suicidal ideation, despite similar defense profiles, when compared to matched heterosexual peers. Additional research is needed to determine the origins of this increased risk, and comprehensive and targeted prevention and intervention programs must be established to ameliorate such risks.     

The determinants of breast-feeding in sri lanka

Breast-feeding is the focus of rapidly growing interest. Research on the determinants of breast-feeding is only beginning. The research in this paper is based on World Fertility Survey data for Sri Lanka. We develop what we believe to be an appropriate probit model and find that there are significant socioeconomic factors that influence breast-feeding, in addition to the demographic factors focused upon in the literature. Moreover, some of them have clear policy implications, which are elaborated herein with respect to labor force, education, family planning and internal migration policies. In the course of the paper we also address a number of generally neglected statistical issues that should be considered in analyzing the determinants of breastfeeding, including problems resulting from digit preference or age heaping, the need to use dichotomous dependent variables, unavoidable truncation biases in the basic data, and structural shifts in the determinants of breastfeeding at different durations.     

CLASS SIZE AND CLASS HETEROGENEITY

We study how class size and class composition affect the academic and labor market performance of college students, two crucial policy questions given the secular increase in college enrollment. Our identification strategy relies on the random assignment of students to teaching classes. We find that a one standard deviation increase in class‐size results in a 0.1 standard deviation deterioration of the average grade. Further, the effect is heterogeneous as it is stronger for males and lower income students. Also, the effects of class composition in terms of gender and ability appear to be inverse U‐shaped. Finally, a reduction of 20 students (one standard deviation) in one’s class size has a positive effect on monthly wages of about €80 ($115) or 6% over the average.     

Identification and Estimation of Stochastic Bargaining Models

Stochastic sequential bargaining models (Merlo and Wilson (1995, 1998)) have found wide applications in different fields including political economy and macroeconomics due to their flexibility in explaining delays in reaching an agreement. This paper presents new results in nonparametric identification and estimation of such models under different data scenarios.     

Sleep and behavioral correlates of napping among young adults: a survey of first-year university students in Madrid, Spain

Objective: Between November 2002 and March 2003, the authors assessed the prevalence and correlates of napping among Spanish university students. Participants: The sample comprised 1,276 first-year university students; the mean age was 18.74 +/- 1.24 years, and 35.45% were men. Methods: The study was cross-sectional, and the students completed self-report, anonymous questionnaires provided during an in-class survey. Results: Almost half (44%) of the sample reported napping (90% did so after lunch for longer than 1 hour). Multiple logistic regression analysis showed that experiencing an irregular sleep-wakefulness pattern, having a morning school schedule, and being male were significant predictor variables of napping. Further significant outcome variables related to napping were having excessive daytime sleepiness, missing classes because of tiredness, better ability to concentrate later in the afternoon, and a perception of deeper nighttime sleep. Conclusions: Habitual napping is common among Spanish university students and associated with an irregular sleep-wakefulness pattern. Taking long postlunch naps seems to be used by students to cope with insufficient sleep and daytime sleepiness.     

Belief system foundations of backward induction

Two justifications of backward induction (BI) in generic perfect information games are formulated using Bonanno's (1992; Theory and Decision 33, 153) belief systems. The first justification concerns the BI strategy profile and is based on selecting a set of rational belief systems from which players have to choose their belief functions. The second justification concerns the BI path of play and is based on a sequential deletion of nodes that are inconsistent with the choice of rational belief functions.     

Evaluating a Case of Parent Separation in Social Services Through a Text Analysis: Clinical and Health Implications

Abstract

The assessment of the family system is very complex, as several factors have to be taken into account: The number of people involved (one or more children), the involvement of other partners, and the presence of legal disputes. Although evaluation practices have increased considerably, it remains difficult for services to prove their effectiveness. The questions that have guided this work have concerned how much and how do the discourses (discursive repertoires) produced by the conflicting parents change as a result of an intervention by the Service? And how much is it possible to evaluate the change in short texts? We used the Methodology for the Analysis of Computerised Text Data (MADIT) methodology that makes it possible to analyze the texts produced by the parents after the Service consultancy. The text is acquired through 14 emails sent by each parent to the other. The results showed that it was possible to detect a change in the repertoires used by the two parents to make decisions regarding their child. This data could increase the use of evaluation in the Services, reducing costs and evaluating change also by email. Future research could apply this methodology in situations where the conflict has not yet exploded and has not had an impact on children.     

Image estimators based on marked bins

The problem of approximating an ‘image’ S?? ^d from a random sample of points is considered. If S is included in a grid of square bins, a plausible estimator of S is defined as the union of the ‘marked’ bins (those containing a sample point). We obtain convergence rates for this estimator and study its performance in the approximation of the border of S. The practical aspects of implementation are discussed, including some technical improvements on the estimator, whose performance is checked through a real data example.     

A Two-Latent-Class Model for Smoking Cessation Data with Informative Dropouts

Non ignorable missing data is a common problem in longitudinal studies. Latent class models are attractive for simplifying the modeling of missing data when the data are subject to either a monotone or intermittent missing data pattern. In our study, we propose a new two-latent-class model for categorical data with informative dropouts, dividing the observed data into two latent classes; one class in which the outcomes are deterministic and a second one in which the outcomes can be modeled using logistic regression. In the model, the latent classes connect the longitudinal responses and the missingness process under the assumption of conditional independence. Parameters are estimated by the method of maximum likelihood estimation based on the above assumptions and the tetrachoric correlation between responses within the same subject. We compare the proposed method with the shared parameter model and the weighted GEE model using the areas under the ROC curves in the simulations and the application to the smoking cessation data set. The simulation results indicate that the proposed two-latent-class model performs well under different missing procedures. The application results show that our proposed method is better than the shared parameter model and the weighted GEE model.