Tucker3 Model for Compositional Data

For the exploratory analysis of three-way data, the Tucker3 is one of the most applied models to study three-way arrays when the data are quadrilinear. When the data consist of vectors of positive values summing to a unit, as in the case of compositional data, this model should consider the specific problems that compositional data analysis brings. The main purpose of this paper is to describe how to do a Tucker3 analysis of compositional data, and to show the relationships between the loading matrices when different preprocessing procedures are used.     

A robust Parafac model for compositional data

Compositional data are characterized by values containing relative information, and thus the ratios between the data values are of interest for the analysis. Due to specific features of compositional data, standard statistical methods should be applied to compositions expressed in a proper coordinate system with respect to an orthonormal basis. It is discussed how three-way compositional data can be analyzed with the Parafac model. When data are contaminated by outliers, robust estimates for the Parafac model parameters should be employed. It is demonstrated how robust estimation can be done in the context of compositional data and how the results can be interpreted. A real data example from macroeconomics underlines the usefulness of this approach.     

What do urban college students really think about health insurance? A qualitative study

Abstract

Objective: To determine barriers and opportunities to health insurance enrollment among an undergraduate students at a large urban university. Participants: Participants were 31 college students enrolled in 4-year and community colleges in the City University of New York (CUNY), and six health services and insurance enrollment specialists who facilitate and assist in the health insurance enrollment process for CUNY students. Methods: Focus groups were conducted with students and in-depth interviews with key informants in May 2017. Results: The research revealed important insights into how students perceive and value insurance and yielded recommendations for the university to improve enrollment of its students. Conclusions: Many colleges can increase student enrollment in health insurance by informing and educating students about the process. Improving enrollment processes can increase insurance rates and improve student population health.     

The impact of early occupational choice on health behaviors

Occupational choice is a significant input into workers’ health investments, operating in a manner that can be either health-promoting or health-depreciating. Recent studies have highlighted the potential importance of initial occupational choice on subsequent outcomes pertaining to morbidity. This study is the first to assess the existence and strength of a causal relationship between initial occupational choice at labor entry and subsequent health behaviors and habits. We utilize the Panel Study of Income Dynamics to analyze the effect of first occupation, as identified by industry category and blue collar work, on subsequent health outcomes relating to obesity, alcohol misuse, smoking, and physical activity in 2005. Our findings suggest blue collar work early in life is associated with increased probabilities of obesity, at-risk alcohol consumption, and smoking, and increased physical activity later in life, although effects may be masked by unobserved heterogeneity. The weight of the evidence bearing from various methodologies, which account for non-random unobserved selection, indicates that at least part of this effect is consistent with a causal interpretation. These estimates also underscore the potential durable impact of early labor market experiences on later health.     

Application of a Biologically-Based RFD Estimation Method to Tetrachlorodibenzo-P-Dioxin (TCDD) Mediated Immune Suppression and Enzyme Induction

The current methods for a reference dose (RfD) determination can be enhanced through the use of biologically-based dose-response analysis. Methods developed here utilizes information from tetrachlorodibenzo- p -dioxin (TCDD) to focus on noncancer endpoints, specifically TCDD mediated immune system alterations and enzyme induction. Dose-response analysis, using the Sigmoid-Emax (EMAX) function, is applied to multiple studies to determine consistency of response. Through the use of multiple studies and statistical comparison of parameter estimates, it was demonstrated that the slope estimates across studies were very consistent. This adds confidence to the subsequent effect dose estimates. This study also compares traditional methods of risk assessment such as the NOAEL/safety factor to a modified benchmark dose approach which is introduced here. Confidence in the estimation of an effect dose (ED₁₀) was improved through the use of multiple datasets. This is key to adding confidence to the benchmark dose estimates. In addition, the Sigmoid-Emax function when applied to dose-response data using nonlinear regression analysis provides a significantly improved fit to data increasing confidence in parameter estimates which subsequently improve effect dose estimates.     

Institutions and the adoption of rights: political and property rights in Colombia

Citizenship rights are the result of specific political bargains between different collective actors and state authorities (Tilly Theory and Society 26(34):599–602, 1997). The political bargains for rights are encoded in institutions, and these institutions develop independently from each other and take organizational characteristics that make certain rights easier to adopt than others. I argue that these institutions vary along two dimensions that affect the extent to which states can adopt rights successfully: one dimension is distributional and the second is the depth or extension of the rules that frame a given right. This article focuses on the institutional differences between property rights, especially land property, and political rights, and on the consequences of those differences on their adoption. I then illustrate my argument with examples from Colombia since 1980.     

A statistical method for synthesizing mediation analyses using the product of coefficient approach across multiple trials

Mediation analysis often requires larger sample sizes than main effect analysis to achieve the same statistical power. Combining results across similar trials may be the only practical option for increasing statistical power for mediation analysis in some situations. In this paper, we propose a method to estimate: (1) marginal means for mediation path a, the relation of the independent variable to the mediator; (2) marginal means for path b, the relation of the mediator to the outcome, across multiple trials; and (3) the between-trial level variance–covariance matrix based on a bivariate normal distribution. We present the statistical theory and an R computer program to combine regression coefficients from multiple trials to estimate a combined mediated effect and confidence interval under a random effects model. Values of coefficients a and b, along with their standard errors from each trial are the input for the method. This marginal likelihood based approach with Monte Carlo confidence intervals provides more accurate inference than the standard meta-analytic approach. We discuss computational issues, apply the method to two real-data examples and make recommendations for the use of the method in different settings.     

Racial and ethnic diversity in senior centers: comparing participant characteristics in more and less multicultural settings

The 2008 Health Indicators Project surveyed a probability sample (N = 1,870) of New York City senior center participants. Attendees of racially and ethnically diverse and nondiverse senior centers were compared across 5 domains: demographics; health and quality of life; social support networks; neighborhood perceptions and engagement; health service access/utilization. Although homogeneous and diverse center participants demonstrate similar health and quality-of-life outcomes, those from diverse centers demonstrate greater risk of social isolation, receive less family support, and more likely seek medical care from hospitals or community clinics. Implications and future directions for research, practice and policy are discussed.