A Systematic Review of Propensity Score Methods in the Social Sciences

The use of propensity scores in psychological and educational research has been steadily increasing in the last 2 to 3 years. However, there are some common misconceptions about the use of different estimation techniques and conditioning choices in the context of propensity score analysis. In addition, reporting practices for propensity score analyses often lack important details that allow other researchers to confidently judge the appropriateness of reported analyses and potentially to replicate published findings. In this article we conduct a systematic literature review of a large number of published articles in major areas of social science that used propensity scores up until the fall of 2009. We identify common errors in estimation, conditioning, and reporting of propensity score analyses and suggest possible solutions.     

Family Influences on the Long Term Post-Disaster Recovery of Puerto Rican Youth

This study focused on characteristics of the family environment that may mediate the relationship between disaster exposure and the presence of symptoms that met DSM-IV diagnostic criteria for symptom count and duration for an internalizing disorder in children and youth. We also explored how parental history of mental health problems may moderate this mediational model. Approximately 18 months after Hurricane Georges hit Puerto Rico in 1998, participants were randomly selected based on a probability household sample using 1990 US Census block groups. Caregivers and children (N?=?1,886 dyads) were interviewed with the Diagnostic Interview Schedule for Children and other questionnaires in Spanish. Areas of the family environment assessed include parent-child relationship quality, parent-child involvement, parental monitoring, discipline, parents’ relationship quality and parental mental health. SEM models were estimated for parents and children, and by age group. For children (4–10 years old), parenting variables were related to internalizing psychopathology, but did not mediate the exposure-psychopathology relationship. Exposure had a direct relationship to internalizing psychopathology. For youth (11–17 years old), some parenting variables attenuated the relation between exposure and internalizing psychopathology. Family environment factors may play a mediational role in psychopathology post-disaster among youth, compared to an additive role for children. Hurricane exposure had a significant relation to family environment for families without parental history of mental health problems, but no influence for families with a parental history of mental health problems.     

Mousetrap: An integrated,open-source mouse-tracking package

Mouse-tracking – the analysis of mouse movements in computerized experiments – is becoming increasingly popular in the cognitive sciences. Mouse movements are taken as an indicator of commitment to or conflict between choice options during the decision process. Using mouse-tracking, researchers have gained insight into the temporal development of cognitive processes across a growing number of psychological domains. In the current article, we present software that offers easy and convenient means of recording and analyzing mouse movements in computerized laboratory experiments. In particular, we introduce and demonstrate the mousetrap plugin that adds mouse-tracking to OpenSesame, a popular general-purpose graphical experiment builder. By integrating with this existing experimental software, mousetrap allows for the creation of mouse-tracking studies through a graphical interface, without requiring programming skills. Thus, researchers can benefit from the core features of a validated software package and the many extensions available for it (e.g., the integration with auxiliary hardware such as eye-tracking, or the support of interactive experiments). In addition, the recorded data can be imported directly into the statistical programming language R using the mousetrap package, which greatly facilitates analysis. Mousetrap is cross-platform, open-source and available free of charge from https://github.com/pascalkieslich/mousetrap-os.     

Observational Context of Mother-Child Interaction: Impact of a stress Context on Emotional Availability

Previous studies have found that a stressful observational context challenges the mother-child relationship, thus highlighting negative interactive behavior. However, the impact of observational context has only been investigated in infants and preschoolers without specifically using the Emotional Availability Scales. Nor have they explored whether the association of mother-child interaction with children’s emotional or behavioral problems depends on the observational context. We observed 140 mothers and their five to 12-year-old children in non-stressful free play and in a stressful task context. In general, dyads showed higher emotional availability in the task context compared to the free play. Specifically, mothers showed higher levels of Sensitivity, Structuring and Nonhostility, but lower levels of Nonintrusiveness during the task compared to the free play context; children showed higher levels of Responsiveness during the task than during free play. After controlling for dyadic stress, contextual effects decreased for all dimensions of emotional availability. The association of mother-child interaction with child problem behavior depended on the observational context. Specifically, we found maternal emotional availability during free play to be more strongly associated with child problem behavior than during the stressful task; however, emotional availability of the child was more strongly associated with problem behavior when obtained during the task. We conclude that context impacts on mother-child interactive behavior and also on the association of mother-child-interaction and child behavior. Stress is a relevant contextual factor influencing mother-child interactive behavior.     

Parents' education and children's achievement: The role of personality

The reasons for the positive association between families' background variables, such as parents' education, and children's academic achievement have not fully been clarified yet. The present study investigates children's intelligence and personality as potential mediators. A sample of 580 German high school students (mean age: M = 17.0; SD = 0.7) indicated the highest education of their parents and completed measures assessing their own personality and intelligence. Children's academic achievement was operationalized by grade point average. Children's intelligence, openness to experience and, marginally, conscientiousness partially mediated the association between parents' education and children's academic achievement. Even after controlling for children's intelligence, the mediating effects of those personality traits held. Results are discussed with regard to potential underlying processes. Copyright © 2010 John Wiley & Sons, Ltd.     

The complexity of satisfiability for fragments of hybrid logic—Part I

The satisfiability problem of hybrid logics with the downarrow binder is known to be undecidable. This initiated a research program on decidable and tractable fragments.In this paper, we investigate the effect of restricting the propositional part of the language on decidability and on the complexity of the satisfiability problem over arbitrary, transitive, total frames, and frames based on equivalence relations. We also consider different sets of modal and hybrid operators. We trace the border of decidability and give the precise complexity of most fragments, in particular for all fragments including negation. For the monotone fragments, we are able to distinguish the easy from the hard cases, depending on the allowed set of operators.     

Human Decisions in Moral Dilemmas are Largely Described by Utilitarianism: Virtual Car Driving Study Provides Guidelines for Autonomous Driving Vehicles

Science and Engineering Ethics - Ethical thought experiments such as the trolley dilemma have been investigated extensively in the past, showing that humans act in utilitarian ways, trying to cause...     

Scoring Depression on a Common Metric: A Comparison of EAP Estimation,Plausible Value Imputation,and Full Bayesian IRT Modeling

There are a growing number of item response theory (IRT) studies that calibrate different patient-reported outcome (PRO) measures, such as anxiety, depression, physical function, and pain, on common, instrument-independent metrics. In the case of depression, it has been reported that there are considerable mean score differences when scoring on a common metric from different, previously linked instruments. Ideally, those estimates should be the same. We investigated to what extent those differences are influenced by different scoring methods that take into account several levels of uncertainty, such as measurement error (through plausible value imputation) and item parameter uncertainty (through full Bayesian IRT modeling). Depression estimates from different instruments were more similar, and their corresponding confidence/credible intervals were larger when plausible value imputation or Bayesian modeling was used, compared to the direct use of expected a posteriori (EAP) estimates. Furthermore, we explored the use of Bayesian IRT models to update item parameters based on newly collected data.     

Analysis of Variance Models with Stochastic Group Weights

The analysis of variance (ANOVA) is still one of the most widely used statistical methods in the social sciences. This article is about stochastic group weights in ANOVA models – a neglected aspect in the literature. Stochastic group weights are present whenever the experimenter does not determine the exact group sizes before conducting the experiment. We show that classic ANOVA tests based on estimated marginal means can have an inflated type I error rate when stochastic group weights are not taken into account, even in randomized experiments. We propose two new ways to incorporate stochastic group weights in the tests of average effects – one based on the general linear model and one based on multigroup structural equation models (SEMs). We show in simulation studies that our methods have nominal type I error rates in experiments with stochastic group weights while classic approaches show an inflated type I error rate. The SEM approach can additionally deal with heteroscedastic residual variances and latent variables. An easy-to-use software package with graphical user interface is provided.