Dyadic Analyses of Preschool‐aged Children's Friendships: Convergence and Differences between Friendship Classifications from Peer Sociometric Data and Teacher's Reports

Peer sociometrics and teachers' friendship reports were compared in 2179 preschool dyads. One hundred twenty of 306 reciprocated friend dyads from peer sociometric data were also identified as good friends by their classroom teachers, and 301 of 600 of non‐reciprocated dyads in peer data were named as friends by one or both classroom teachers (overall kappa = .16). Friendship classifications from both peer and teacher data had significant relations with variables relevant to peer interactions, social skills, peer acceptance, and teacher‐rated scales (six of seven tests significant for peer data; five of eight significant for teacher data). Multilevel analyses indicated that friendship status effects were not qualified by classroom‐level differences. Findings suggest that sociometric tasks can identify preschoolers' peer friendships and that the range of correlates may be broader in peer‐choice data than in teachers' friendship evaluations.     

Ambulance allocation for maximal survival with heterogeneous outcome measures

This paper proposes new models for locating emergency medical services (EMS) by incorporating survival functions for capturing multiple-classes of heterogeneous patients. The Maximal Expected Survival Location Model for Heterogeneous Patients (MESLMHP) aims to maximize the overall expected survival probability of multiple-classes of patients, whereby different classes could be defined according to agreed patient categories based on response time targets, or by capturing differing medical conditions each with a corresponding survival function. Furthermore, we propose and demonstrate an approximation approach to solving the extended stochastic version of MESLMHP, which utilizes queuing theory to permit the modeling of congestion and utilization at each ambulance station, and does not require assumptions to be made on the utilization of ambulances. Both models are demonstrated using data from the ambulance service in Wales. We show that our multiple outcome measures and survival-maximizing approach, rather than one based on average response time targets alone or a single patient class provides more effective EMS ambulance allocations.     

Exploring gaps in the online economic inclusion of persons with disabilities in Korea

ABSTRACT

This paper explores the difference in the online economic activities of people with and without disabilities in Korea. We conducted a multiple regression analysis to investigate the impact of socioeconomic characteristics, internet access, and internet skills on online economic activities. Our sample, based on a 2016 dataset that included 1554 people with disabilities and 6004 people without disabilities, was developed using quota sampling based on gender, age, and residence. We determined that individuals with disabilities were more likely to engage in online economic activities if they had higher levels of education, lived in urban areas, were employed, or had greater internet skills. Individuals without disabilities were more likely to engage in online economic activities if they were women, had higher levels of education, were employed, lived in a two-generation or more household, or had greater internet skills. For both people with and without disabilities, the level of education, employment status, and internet skills positively contribute to online economic activites. We also determined that education level, participation in economic activity, living in a two-generation or more household, and internet skills had a statistically significant influence on online economic activity for people both with and without disabilities. These results highlight the importance of education and internet training for people with disabilities, as well as social support systems that help them learn to use the internet in diverse ways through both formal and informal networks. The study also underscores the importance of information and communications technology that adequately addresses people’s needs.     

Trend smoothness achieved by penalized least squares with the smoothing parameter chosen by optimality criteria

This work presents a study about the smoothness attained by the methods more frequently used to choose the smoothing parameter in the context of splines: Cross Validation, Generalized Cross Validation, and corrected Akaike and Bayesian Information Criteria, implemented with Penalized Least Squares. It is concluded that the amount of smoothness strongly depends on the length of the series and on the type of underlying trend, while the presence of seasonality even though statistically significant is less relevant. The intrinsic variability of the series is not statistically significant and its effect is taken into account only through the smoothing parameter.     

Trauma and health risk behaviors in people with severe mental illness

The current study tests the association between a composite measure of unsafe sex and sharing syringes for drug use with six of the more common lifetime traumatic/stressful events in 421 community mental health clients with severe mental illness (SMI) while controlling for psychiatric symptoms and related problems. A small but significant proportion of respondents said they had injected drugs with a shared needle in their lifetime (30, 7.2%), and a much larger proportion of respondents had engaged in unprotected sex (165, 39.2%). Unprotected sex and needle sharing were significantly correlated (Spearman’s rho = .20, p < .01). Frequency of lifetime traumatic events that occurred at least once was reported by one third to three quarters of clients depending on type of trauma. Regression analysis revealed that substance abuse and lifetime homelessness were significantly correlated with health risk behaviors. Practitioners need to be continuously vigilant to comorbid substance use and the housing needs of people with SMI. Limitations of the study include its cross-sectional design.     

The effect of fast and slow decisions on risk taking

We experimentally compare fast and slow decisions in a series of experiments on financial risk taking in three countries involving over 1700 subjects. To manipulate fast and slow decisions, subjects were randomly allocated to responding within 7 seconds (time pressure) or waiting for at least 7 or 20 seconds (time delay) before responding. To control for different effects of time pressure and time delay on measurement noise, we estimate separate parameters for noise and risk preferences within a random utility framework. We find that time pressure increases risk aversion for gains and risk taking for losses compared to time delay, implying that time pressure increases the reflection effect of Prospect Theory. The results for gains are weaker and less robust than the results for losses. We find no significant difference between time pressure and time delay for loss aversion (tested in only one of the experiments). Time delay also leads to less measurement noise than time pressure and unconstrained decisions, and appears to be an effective way of decreasing noise in experiments.     

Environmental and Behavioral Circumstances and Consequences of Falls in a Senior Living Development

This article investigated the role of environmental and behavioral factors surrounding fall incidents in a senior living community. Using a mixed-methods approach, this research included both a retrospective analysis of fall reports and resident interviews. The quantitative analysis showed falls in the bedroom and bathroom were more likely to happen between 12 am and 8 am. Falls in the bathroom were more likely to result in severe injuries compared to falls in other rooms. The qualitative analysis identified three types of fall-related activity (transfer, ambulation, standing) and five behavioral factors surrounding fall incidents (transferring, slipping, misjudged behavior, tripping, health issue).     

Discovering hidden statistical issues through individual-level models in ecological studies

ABSTRACT

In ecological studies, individual inference is made based on results from ecological models. Interpretation of the results requires caution since ecological analysis on group level may not hold in the individual level within the groups, leading to ecological fallacy. Using an ecological regression example for analyzing voting behaviors, we highlight that the explicit use of individual-level models is crucial in understanding the results of ecological studies. In particular, we clarify three relevant statistical issues for each individual-level models: assessment of the uncertainty of parameter estimates obtained from a wrong model, the use of shrinkage estimation method for simultaneous estimation of many parameters, and the necessity of sensitivity analysis rather than adhering to one seemingly most compelling assumption.