Inflated beta distributions

This paper considers the issue of modeling fractional data observed on [0,1), (0,1] or [0,1]. Mixed continuous-discrete distributions are proposed. The beta distribution is used to describe the continuous component of the model since its density can have quite different shapes depending on the values of the two parameters that index the distribution. Properties of the proposed distributions are examined. Also, estimation based on maximum likelihood and conditional moments is discussed. Finally, practical applications that employ real data are presented.     

Predicting Severity of Foreign Body Injuries in Children in Upper Airways: An Approach Based on Regression Trees

The entry of a small item into the upper airways is one of the leading causes of injuries in children up to 14 years old. The aim of this study is to characterize types of objects causing choking along with the features of the children involved in the accident and compare results with current standards. The European Survey on Foreign Bodies Injuries Study (ESFBI) collected data on foreign body injuries from 19 European countries. The data from ESFBI were selected according to the ICD-9-CM codes 933 (foreign body in the pharynx and larynx) and 934 (foreign body in the trachea, bronchi, and lungs). Both a classification tree and a linear discriminant analysis (LDA) have been set up to predict the probability that an injured child experiences a hospitalization. The classification tree provides flowchart-type decision rules and allows for analyzing the impact of the item features, the children characteristics, and the circumstances of the accidents on the severity of the foreign body injuries. Results showed that children younger than 3.5 who are involved in an accident have a high probability to experience a hospitalization.     

A Gender Lens on Quality of Life: The Role of Sense of Community,Perceived Social Support,Self-Reported Health and Income

Quality of life (QoL) refers to a subjective evaluation that is embedded in a cultural, social and environmental context. It is a multidimensional concept and its assessment covers four domains: physical health, psychological health, social relationships, and environment. Although many studies report on QoL, literature rarely addressed the question of the QoL predictors from a gender perspective. Present study aimed at investigating gender differences in the determinants of QoL. Specifically, gender was considered as a moderator in the relationship between predictors of QoL (i.e. socio-demographic characteristics, perceived health, income, social support and sense of community) and each dimension of QoL. 654 Italian adults participated in the study. Results show that men outscore women on the physical, the psychological and the environmental domains of QoL. Considering determinants of QoL, sense of community and self-reported health operate in a similar fashion for both genders. On the contrary, social support is more predictive for women’s QoL, whereas the income level is more significant for men’s QoL. Implications are discussed.     

Psychometric Properties of the Medical Outcome Study Social Support Survey with a General Population Sample of Undergraduate Students

Among non-clinical populations, perceived social support is an important factor in health maintenance and well-being. Among measures that purport to assess perceived social support, the Medical Outcomes Study Social Support Survey (MOS-SSS) is based on a strong conceptual framework and has been subjected to a rigorous psychometric evaluation. Since no studies have investigated its psychometric properties with a young, non-clinical population, the purpose of this study is to investigate the psychometric properties (construct validity, internal consistency, and test–retest reliability) of an Italian version of the MOS-SSS with a non-clinical population sample. A convenience sample of 485 undergraduate students (73.0 % female; mean age = 21.81 ± 1.52) has been recruited. With regards to scale dimensionality, the best fit measurement model found support for the four subscales proposed by the original version: emotional and informational support, tangible support, positive social interactions, and affectionate support (χ ²/df = 4.49; CFI = .92; TLI = .91; RMSEA = .08). MOS-SSS subscales showed good internal consistency (Cronbach’s alpha for the subscales ranged from .848 to .939). Significant correlations were found with measures of psychological well-being (Ryff’s Scales of Psychological Well-Being) and depression (Beck-Depression Inventory-II). Test–retest stability was tested by examining a subsample (N = 225) over a 10-week period (correlation coefficients for the subscales ranged from .502 to .579). The findings suggest that MOS-SSS presents good psychometric characteristics with a young general population sample. Therefore, the MOS-SSS seems to be a psychometrically sound measure for the evaluation of perceived social support among young non-clinical populations.     

Comparison of Modes of Administration and Response Options in the Assessment of Subjective Health Using the First Question of SF-36

To compare two modes of administration (self-administered; by interviewer) and two response options format (using words; images of “facial-expressions”) of the first question of SF-36 (Q1SF-36), and to test its validity. We included 825 participants (20–90 years). Q1SF-36, using words or images, was included in a global questionnaire interview and at the end participants filled the SF-36. The agreement was tested by weighted kappa coefficients (WKappa). Classification Trees were used in the calibration of Q1SF-36 responses, with the physical (PDSF36) and mental dimensions of SF-36. Polyserial correlation coefficients and areas under the ROC curves (AUC) were used for validation. After categorization, using PDSF36 classification trees, the WKappa were 0.770 (self-administered vs. interviewer), 0.569 (self-administered vs. facial-expressions) and 0.566 (interviewer vs. facial-expressions). The WKappa between the PDSF36 and the modes (self-administered, interviewer and facial-expressions) were 0.784, 0.713 and 0.579 and the corresponding polyserial correlation coefficients were 0.784, 0.713 and 0.579. A good discriminatory power was found comparing the modes with the PDSF36 (AUC = 0.907, 0.923 and 0.827), but not with mental dimension (AUC = 0.538, 0.501 and 0.629). The Q1SF-36, by self-administration or interviewer, may be a valid alternative for assessment of subjective physical health, but not mental health.     

The Gamma-count distribution in the analysis of experimental underdispersed data

Event counts are response variables with non-negative integer values representing the number of times that an event occurs within a fixed domain such as a time interval, a geographical area or a cell of a contingency table. Analysis of counts by Gaussian regression models ignores the discreteness, asymmetry and heteroscedasticity and is inefficient, providing unrealistic standard errors or possibly negative predictions of the expected number of events. The Poisson regression is the standard model for count data with underlying assumptions on the generating process which may be implausible in many applications. Statisticians have long recognized the limitation of imposing equidispersion under the Poisson regression model. A typical situation is when the conditional variance exceeds the conditional mean, in which case models allowing for overdispersion are routinely used. Less reported is the case of underdispersion with fewer modeling alternatives and assessments available in the literature. One of such alternatives, the Gamma-count model, is adopted here in the analysis of an agronomic experiment designed to investigate the effect of levels of defoliation on different phenological states upon the number of cotton bolls. Data set and code for analysis are available as online supplements. Results show improvements over the Poisson model and the semi-parametric quasi-Poisson model in capturing the observed variability in the data. Estimating rather than assuming the underlying variance process leads to important insights into the process.     

“Trying to be positive in the face of the storm”: The experiences of independent college students during the COVID-19 pandemic

The COVID-19 pandemic created multiple stressors for college students, particularly for young adults experiencing multiple forms of disadvantage. Little is known about the pandemic experiences of independent college students, many of whom are emancipated minors, former wards of the state, and other students who lack familial financial and practical support as they pursue higher education. Twenty-three independent students, ages 18–23, from one northeastern university were interviewed to understand how independent students were affected by the COVID-19 pandemic, and their needs for support from the university during this time. Most participants were identified as Black or Latinx, and two thirds were first-generation college students. Participants reported an overall lack of support from their families prior to the pandemic. During the pandemic, they experienced compounding academic, economic, and mental health-related stressors. Students responded to these stressors in resilient and resourceful ways, by adapting to their new realities, expressing gratitude, and finding opportunities for self-growth. Participants recommend that institutions of higher education support independent students during periods of emergency through providing financial assistance, offering opportunities for connection with both adults and peers, and demonstrating administrative flexibility and understanding of their unique needs.