Ranked sparsity: a cogent regularization framework for selecting and estimating feature interactions and polynomials

AStA Advances in Statistical Analysis - We explore and illustrate the concept of ranked sparsity, a phenomenon that often occurs naturally in modeling applications when an expected disparity exists...     

Cognitive reappraisal and need to belong predict prosociality in Mexican-origin adolescents

This 2-year longitudinal study examined Mexican-origin adolescents’ need to belong and cognitive reappraisal as predictors of multiple forms of prosocial behavior (i.e., general, emotional, and public prosocial behaviors). Prosocial behaviors, which are actions intended to benefit others, are hallmarks of social proficiency in adolescence and are influenced by intrapersonal abilities and motivations that typically develop during adolescence. Yet, few studies of Mexican-origin or other U.S. Latinx youths have examined whether such individual difference characteristics, specifically social motivation and emotion regulation skills, support prosocial behavior. In a sample of 229 Mexican-origin youth (M_age = 17.18 years, SD = .42, 110 girls), need to belong, cognitive reappraisal, and general prosocial behaviors were assessed at ages 17 and 19. Emotional and public forms of prosociality also were assessed at age 19. Cognitive reappraisal was positively associated with concurrent general prosociality at age 17, whereas need to belong was positively associated with concurrent public prosociality at age 19. Moderation analyses revealed that general and emotional types of prosocial behaviors at age 19 were lowest for youth with both lower need to belong and less use of cognitive reappraisal at 19 years. Greater cognitive reappraisal skills and need to belong may reflect distinct motivations for engaging in varying forms of prosocial behavior in late adolescence.     

Bayesian modelling of effects of prenatal alcohol exposure on child cognition based on data from multiple cohorts

High levels of prenatal alcohol exposure (PAE) result in significant cognitive deficits in children, but the exact nature of the dose-response relationship is less well understood. To investigate this relationship, data were assembled from six longitudinal birth cohort studies examining the effects of PAE on cognitive outcomes from early school age through adolescence. Structural equation models (SEMs) are a natural approach to consider, because of the way they conceptualise multiple observed outcomes as relating to an underlying latent variable of interest, which can then be modelled as a function of exposure and other predictors of interest. However, conventional SEMs could not be fitted in this context because slightly different outcome measures were used in the six studies. In this paper we propose a multi-group Bayesian SEM that maps the unobserved cognition variable to a broad range of observed outcomes. The relation between these variables and PAE is then examined while controlling for potential confounders via propensity score adjustment. By examining different possible dose-response functions, the proposed framework is used to investigate whether there is a threshold PAE level that results in minimal cognitive deficit.