Multilevel covariance structure analysis of sibling substance use and intrafamily conflict

Conventional covariance structure analysis, such as factor analysis, is often applied to data that are obtained in a hierarchical fashion, such as siblings observed within families. A more appropriate specification is demonstrated which explicitly models the within-level and between-level covariance matrices of sibling substance use and intrafamily conflict. Participants were 267 target adolescents (mean age=13.11 years) and 318 siblings (mean age=15.03 years). The level of homogeneity within sibling clusters, and heterogeneity among families, was sufficient to conduct a multilevel covariance structure analysis (MCA). Parental and family-level variables consisting of marital status, socioeconomic status, marital discord, parent use, and modeling of substances were used to explain heterogeneity among families. Marital discord predicted intrafamily conflict, and parent marital status and modeling of substances predicted sibling substance use. Advantages and uses of hierarchical designs and conventional covariance structure software for multilevel data are discussed.     

Linear structural equations with latent variables

An interdependent multivariate linear relations model based on manifest, measured variables as well as unmeasured and unmeasurable latent variables is developed. The latent variables include primary or residual common factors of any order as well as unique factors. The model has a simpler parametric structure than previous models, but it is designed to accommodate a wider range of applications via its structural equations, mean structure, covariance structure, and constraints on parameters. The parameters of the model may be estimated by gradient and quasi-Newton methods, or a Gauss-Newton algorithm that obtains least-squares, generalized least-squares, or maximum likelihood estimates. Large sample standard errors and goodness of fit tests are provided. The approach is illustrated by a test theory model and a longitudinal study of intelligence.This investigation was supported in part by a Research Scientist Development Award (KO2-DA00017) and a research grant (DA01070) from the U. S. Public Health Service.     

Development of Adolescent Problem Behavior

The developmental model of adolescent antisocial behavior advanced by Patterson and colleagues (e.g., Patterson, Reid, & Dishion, 1992) appears to generalize the development of a diverse set of problem behaviors. Structural equation modeling methods were applied to 18-month longitudinal data from 523 adolescents. The problem behavior construct included substance use, antisocial behavior, academic failure, and risky sexual behavior. Families with high levels of conflict were less likely to have high levels of parent–child involvement. Such family conditions resulted in less adequate parental monitoring of adolescent behavior, making associations with deviant peers more likely. Poor parental monitoring and associations with deviant peers were strong predictors of engagement in problem behavior. These constructs accounted for 46% of the variance in problem behavior. Although association with deviant peers was the most proximal social influence on problem behavior, parental monitoring and family factors (conflict and involvement) were key parenting practices that influenced this developmental process.     

Classical test theory based and factor analytic structural models for analyzing change: A note on differences and similarities

This note is concerned with differences and similarities between structural models for analyzing change, which are conceptualized within two different modelling traditions: the one based on the classical test theory, and that within the factor-analytic approach. It is shown that these two possibilities lead to models for studying change, which are indistinguishable when using for data analytic purposes structural modeling programs, such as LISREL, EQS, COSAN, LISCOMP, RAMONA, EzPATH, SAS PROC CALIS. The reason for this data-analytic equivalence of the two conceptually different types of models is the confounding of their differences in the corresponding implied covariance matrix structures.     

On the need for structurally competent counselling and psychotherapy: Neoliberal ideology,disability and the psy disciplines

This article highlights and problematises the psy disciplines' articulations with neoliberalism, with a particular focus upon disability and upon counselling and psychotherapy. Recent years have witnessed burgeoning scholarly interest in the potential complicities of the psy professions in a neoliberal agenda of individualisation, pathologisation and responsibilisation of human suffering. Such complicities are, in state therapy settings, driven by a growing need for these professions to offer cost-effective, evidence-based interventions to secure funding in an increasingly competitive market. Whilst the entwining of neoliberal ideology with therapy practices may be innocuous for some, it is contended that disabled people may be at particular risk of harm. A case is then made for training and practice to foreground structural competency, an awareness of how therapy encounters and client concerns are shaped by socio-structural factors, including, but not limited to, politics and political ideology. This would require not only an appreciation of the sociopolitical context in which therapy unfolds and its indubitable shaping of subjectivities, but also greater recognition of disability as a source of social inequity and oppression, as opposed to an individual phenomenon. Moreover, structural competency would require theoretical and demographic diversity in training and practice, which, in turn, would necessitate identifying and addressing barriers to inclusion for disabled people. Points raised are deemed of particular importance given the emergence of long COVID.     

Haitian and Haitian American experiences of racism and socioethnic discrimination in Miami-Dade county: At-risk and court-involved youth

We examine how juvenile justice-involved youth of Haitian descent in Miami-Dade County cope with structural racism and its impact on their mental health. Drawing on longitudinal ethnography, psychosocial assessment data, and a family-based clinical intervention funded by the National Institute on Drug Abuse, this article explores youth narratives of discrimination prior to and during the COVID-19 pandemic. We use critical race theory and theory of practice to understand youths’ perceptions as racialized bodies and stigmatized selves, highlighting the experiences and perspectives of a particular black immigrant group, ethnic beings caught up in the everyday practices of racialization, sociocultural marginalization, and racism. We frame these experiences as a variation of the complex continuum of structural racism and racial domination in the US. These experiences have caused anger, fear, anxiety, chronic anticipatory distress, and hopelessness among youth of Haitian descent. We conclude with some recommendations for therapeutic support that encourages youth to process their experiences, promotes their development of a positive self-concept, and provides them with mind-body techniques to attenuate the physical impacts of discriminatory events. The clinical trial registration number for this study intervention is NCT03876171.     

Dyadic longitudinal models: A critical review

In this review, we discuss the most commonly used models to analyze dyadic longitudinal data. We start the review with a definition of dyadic longitudinal data that allows relationship researchers to identify when these models might be appropriate. Then, we go on to describe the three major models commonly used when one has dyadic longitudinal data: the dyadic growth curve model (DGCM), the actor–partner interdependence model (APIM), and the common fate growth model (CFGM). We discuss when each model might be used and strengths and weaknesses of each model. We end with additional thoughts that focus on extensions to new methods being discussed in the literature, along with some of the challenges of collecting and analyzing dyadic longitudinal data that might be helpful for future dyadic researchers.     

识字能力的单维性检验研究

本研究以义务教育阶段学生识字量测验为工具,综合运用探索性结构方程建模(ESEM)以及非参数项目反应理论中的摩根量表(Mokken量表)和DETECT分析方法,探讨了识字能力的维度。探索性结构方程建模结果显示,识字的单维性模型优于多维模型,多维的结果更多的体现出一个难度维度的特征,即字频的作用。Mokken量表分析结果显示,1~2年级和3~9年级测验更倾向于单维量表的特征。DETECT分析结果显示,两个测验的D值趋近于零,表明识字能力是单维能力。结合三种分析方法,识字能力具有单维性。     

关于自尊结构模型的理论建构

本文在已有研究基础上建构了自尊结构的“倒立金字塔”理论模型,该模型由潜在自尊、社会自尊和元自尊三个维度组成,它们之间的关系既是独立的,又相互协调、互相影响。自尊结构模型中的每一层结构的作用都是建立在它下一层结构作用的基础之上的,这既体现了信息加工系统的经验结构思想,又反映了人自尊系统的特性与机制,同时也更能表征自尊内在结构的驱动性、社会性与调节性特点。     

The Graded Response Differential Discrimination Model Accounting for Extreme Response Style

Extreme response style or, more generally, individual differences in response spacing have been shown to be an influential bias when analyzing questionnaire data. Recently a promising model adjusting for this bias — the differential discrimination model — has been proposed. An advantage to other related approaches is that the model can be fitted using standard structural equation modeling software. However, the model is designed for analyzing continuous item responses, whereas graded response formats are certainly more prominent in behavioral sciences. To resolve this limitation, the present article extends the differential discrimination model to analyzing graded responses. Empirical examples as well as a small simulation study are presented.