Latent Variable Interaction Research Articles

Are perfectionistic strivings beneficial or detrimental to well-being and achievement? Tests of procrastination and emotion regulation as moderators.

Researchers have called for an approach that examines the conditions under which perfectionistic strivings (PS) may be beneficial or detrimental to psychological functioning. We adopted a self-regulation perspective and tested whether individual differences in self-regulation (procrastination, emotion regulation) moderate PS's relationships with achievement and well-being in an academic/work-related achievement context. A sample of 183 preservice teachers participated in a study that combined "traditional" longitudinal assessment (six performance situations over a 9-month period) with repeated ambulatory assessment (measuring well-being, procrastination, and emotion regulation during a total of 910 preparation phases that preceded performance situations). Mean levels of achievement, well-being, and emotion regulation were found to be stable over time, whereas procrastination decreased on average across preparation phases. Results from latent variable interaction models indicated that individual differences in intraindividual change in procrastination over time moderated the relationship between PS and well-being (but not achievement) in the expected direction: The less individuals decreased in procrastination over time, the more negative the relationship between PS and well-being was. Contrary to expectations, we found no evidence of a moderating effect of emotion regulation. The study contributes to a nuanced perspective on the adaptiveness of PS.

Childhood Violence, High School Academic Environment, and Adult Alcohol Use Among Latinas and Black Women: A Structural Equation Modeling Study.

Young Latinas and Black women drink less than women of other racial/ethnic groups but experience more alcohol-related problems in midlife. This study aims to identify modifiable factors to prevent adult onset of alcohol use disorder (AUD) in this population. Data were collected at six time points as part of the Harlem Longitudinal Development Study from 365 Latinas (47%) and Black (53%) women (mean age at time 1 = 14, standard deviation 1.3). Structural equation modeling was used to test hypothesized pathways from childhood physical and sexual abuse to AUD via depressive mood, anxiety disorders, and somatic complaints in the 20s. We also tested the moderation effect of the high school academic environment by including in the structural equation model two latent variable interaction terms between the school environment and each of the abuse variables. Childhood physical and sexual abuse was positively associated with depressive mood, anxiety disorders, and somatic complaints when participants were in the 20s. Depressive mood mediated childhood abuse and AUD when women were in the 30s. The high school academic environment attenuated the effect of physical, but not sexual abuse, on depressive mood (β = -0.59, B = -9.38, 95% CI [-14.00, -4.76]), anxiety symptoms (β = -0.61, B = -14.19, 95% CI [-21.76, -6.61]), appetite loss (β = -0.41, B = -10.52, 95% CI [-15.61, -5.42]), and sleeplessness (β = -0.50, B = -9.56, 95% CI [-13.95, -5.17]) in the early 20s. Our findings underscore the need to invest in early violence prevention interventions and in education to ensure equitable access to quality, academically oriented, and safe schools.

Structural Equation Modeling in Organizational Research: The State of Our Science and Some Proposals for Its Future

The use of structural equation modeling (SEM) has grown substantially over the past 40 years within organizational research and beyond. There have been many different developments in SEM that make it increasingly useful for a variety of data types, research designs, research questions, and research contexts in the organizational sciences. To give researchers a better understanding of how and why SEM is used, our article ( a) presents a review of SEM applications within organizational research; ( b) discusses SEM best practices; and ( c) explores advanced SEM applications, including instrumental variable methods, latent variable interactions and nonlinear measurement models, multilevel SEM, cross-lagged panel models and dynamic structural equation models, and meta-analytic SEM. We conclude by discussing concerns and debates that are both methodological (i.e., cross-validation and regularization) and theoretical (i.e., understanding causal evidence) as they relate to SEM and its application in organizational research and beyond.

An evaluation of methods to handle missing data in the context of latent variable interaction analysis: multiple imputation, maximum likelihood, and random forest algorithm

An evaluation of methods to handle missing data in the context of latent variable interaction analysis: multiple imputation, maximum likelihood, and random forest algorithm

She Asked for It: Hardcore Porn, Sexism, and Rape Myth Acceptance.

The present study examined pornography viewing, rape myth acceptance, and sexist attitudes. Data came from 392 male and 903 female participants. Multigroup SEM indicated neither pornography viewing, nor hardcore pornography viewing, were related to rape myth acceptance when controlling for sexist attitudes among men. Wald tests indicated hostile sexism to be a significantly stronger predictor of all rape myths examined compared to pornography viewing or hardcore pornography viewing in men and women. Latent variable interaction analyses suggested hardcore pornography viewing as a significant exacerbating factor for the relationship between hostile sexism and "she asked for it" rape myths across genders.

Testing and Interpreting Latent Variable Interactions Using the semTools Package

Examining interactions among predictors is an important part of a developing research program. Estimating interactions using latent variables provides additional power to detect effects over testing interactions in regression. However, when predictors are modeled as latent variables, estimating and testing interactions requires additional steps beyond the models used for regression. We review methods of estimating and testing latent variable interactions with a focus on product indicator methods. Product indicator methods of examining latent interactions provide an accurate method to estimate and test latent interactions and can be implemented in any latent variable modeling software package. Significant latent interactions require additional steps (plotting and probing) to interpret interaction effects. We demonstrate how these methods can be easily implemented using functions in the semTools package with models fit using the lavaan package in R, and we illustrate how these methods work using an applied example concerning teacher stress and testing.

The mechanisms of interest and perseverance in predicting achievement among academically resilient and non-resilient students: Evidence from Swedish longitudinal data.

Students with low socio-economic status (SES) are typically depicted as low performers and more likely to fail in school. However, a group of students, despite their background, manage to succeed in school. The capacity to overcome adversities and achieve successful educational outcomes is referred to as Academic Resilience. Research on the relationship between personality traits and academic performance shows that conscientiousness is a crucial factor in predicting academic success and resilience. However, it has also been shown that achievement is a result of an interaction between conscientiousness and students' interest in the subject. The study aims to investigate how students' school-related perseverance and interest predict academic achievement among resilient and non-resilient pupils over time in the Swedish compulsory school setting. Study subjects were a subset (N = 1,665) of the sampled compulsory school students from the 1992 birth cohort in the evaluation through follow-up (ETF) database. Multigroup structural equationmodelling (SEM) with latent variable interaction was used. Measurement invariance was tested to examine the comparability of the constructs across groups. The results suggest that resilient students rely heavily on both perseverance of effort and interest in school subjects to succeed in their education. For the non-resilient group, the later perseverance level was conditioned on the level of the interest, and neither their early nor later grade interest was related to their achievement. The academically resilient students displayed more consistency in interest and perseverance over time, which might explain their relative success compared to the non-resilient group.

Family Processes, Parenting Practices, and Psychosocial Maturity of Chinese Youths: A Latent Variable Interaction and Mediation Analysis.

Development of psychosocial maturity has profound implications for youths’ well-being and positive development in the long run. Nevertheless, little research has investigated the way family socialization contributes to youths’ psychosocial maturity. Both the concepts of family socialization and psychosocial maturity are multifaceted and latent, which may lead to biased results if studied by manifest variables. Also, no existing research has discovered how different family socialization components interact latently to contribute to youths’ psychosocial maturity. The current study, based on a sample of 533 Chinese parent-youth dyads, examined the effects of family socialization by positive family processes and authoritative parenting, and their latent interaction in an integrated moderation and mediation modeling framework on Chinese youths’ psychosocial maturity. Results showed that both positive family processes and authoritative parenting, and their latent interaction significantly predicted the higher psychosocial maturity of Chinese youths. Authoritative parenting acted as a mediator for the relationship between positive family processes and Chinese youths’ psychosocial maturity. Furthermore, the mediating effect of authoritative parenting was conditioned by different contexts of positive family processes, the strongest and least strong effects found in high and low positive family processes, respectively, and moderate effect observed in medium positive family processes. Findings of the current study contribute to our understanding of the complicated family mechanism in relation to youth development, especially in this digital era.

Bayesian estimation of single and multilevel models with latent variable interactions

ABSTRACT In this article, we discuss single and multilevel SEM models with latent variable interactions. We describe the Bayesian estimation for these models and show through simulation studies that the Bayesian method outperforms other methods such as the maximum-likelihood method. We show that multilevel moderation models can easily be estimated with the Bayesian method.

CB-SEM latent interaction: Unconstrained and orthogonalized approaches

Covariance Based – Structural Equation Modelling (CB-SEM) is often used to investigate moderation and latent interaction effects. This study illustrates and compares the application of constrained, unconstrained and orthogonalized CB-SEM approaches to latent variable interaction analysis using AMOS. Although all three techniques provided similar parameter estimates, the orthogonalized approach provided reduced standard errors resulting in identifying a significant latent interaction, suggesting the orthogonalized approach may be better suited for exploratory research.The illustrated example demonstrates three CB-SEM techniques, and the simplicity of the three approaches to test for interaction effects. The three approaches can be comfortably implemented in available software programs. Guidelines and recommendations for the use of the three approaches are identified with a step-wise process of assessing the latent interaction effect in CB-SEM.As far as we are aware this is the first investigation comparing and recommending specific CB-SEM latent variable moderation analysis techniques in marketing research.

Process and context: Longitudinal effects of the interactions between parental involvement, parental warmth, and SES on academic achievement

Parents' involvement in their children's education and parental warmth have been linked to many positive child outcomes. In addition to these positive associations, contemporary developmental theory stresses the interaction between different parenting variables and the interaction between parenting and broad contextual factors such as family socioeconomic status (SES). Thus, the purpose of this study was to examine main and interaction effects of parent home-based involvement and parental warmth on achievement outcomes. Additionally, we evaluated whether these variables also interacted with SES to predict students' achievement growth. Using the Early Childhood Longitudinal Study – Kindergarten Cohort of 2010–11 (N = 2352), growth of academic outcomes was modeled from kindergarten to the fourth grade. We then used latent variable interaction (Maslowsky, Jager, & Hemken, 2015) procedures to examine interaction effects of our primary study variables. Few significant effects were noted for children's reading and mathematics scores, but more substantial main (home-based involvement) and interaction (parental warmth and SES) effects emerged for science achievement. At high SES levels, warmth negatively predicted growth in science, whereas at lower SES levels, warmth positively predicted growth. Findings are discussed in relation to importance of parent involvement, differential effects across SES contexts, and curricular emphasis in contemporary schools.

A Two-level Moderated Latent Variable Model with Single Level Data

With single-level data, Yuan, Cheng and Maxwell developed a two-level regression model for more accurate moderation analysis. This article extends the two-level regression model to a two-level moderated latent variable (2MLV) model, and uses a Bayesian approach to estimate and test the moderation effects. Monte Carlo results indicate that: 1) the new method yields more accurate estimate of the interaction effect than those via the product-indicator (PI) approach and latent variable interaction (LVI) with single-level model, both are also estimated via Bayesian method; 2) the coverage rates of the credibility interval following the 2MLV model are closer to the nominal 95% than those following the other methods; 3) the test for the existence of the moderation effect is more reliable in controlling Type I errors than both PI and LVI, especially under heteroscedasticity conditions. Moreover, a more interpretable measure of effect size is developed based on the 2MLV model, which directly answers the question as to what extent a moderator can account for the change of the coefficient between the predictor and the outcome variable. A real data example illustrates the application of the new method.

The well-being of China’s rural to urban migrant children: Dual impact of discriminatory abuse and poverty

BackgroundPost-migration experiences of discriminatory abuse and poverty have been recognized as key risk factors for psychopathology and health problems among children. However, little research has explored these associations among children participating in the internal migration process. Building on the stress and coping framework (Lazarus & Folkman, 1984), this study investigated the influence of discriminatory abuse and poverty on depressive symptoms and health problems in a group of Chinese migrant children. It also examined how a culturally based meaning-focused coping, as measured by Chinese beliefs about adversity scale, moderates the stress-distress associations. ParticipantsA cross-sectional study was conducted among 1714 migrant youth (Mean Age = 13; Range = 10–16; 45.6 % Female). MethodsThe latent variable interaction structural equation modeling was conducted to explore the main and interaction effects among studied variables. ResultsHigh prevalence of depressive symptoms (49.6 %) was found for this sample. More than 90% of respondents reported on an average of 0–2 days as being sick over the past 30 days. Migrant youth were found to experience moderate levels of discriminatory abuse (M = 1.29, SD = 0.51; Range = 1–4) and economic stress (M = 1.38, SD = 1.25; Range = 1–4). The findings further revealed that discriminatory abuse and economic stress possessed severe consequences on their mental and physical health. The meaning-focused coping strategy weakened the relationship between discriminatory abuse and depressive symptoms (β=-0.07, p<.001). Among migrant youth who encountered discriminatory abuse those who adhered more to meaning-focused coping reported less depressive symptoms. ConclusionFindings shed light on the protective role of cultural factors in stress management for young people from migrant backgrounds.

How Are We Testing Interactions in Latent Variable Models? Surging Forward or Fighting Shy?:

Latent variable models and interaction effects have both been common in the organizational sciences for some time. Methods for incorporating interactions into latent variable models have existed si...

How Are We Testing Interactions in Latent Variable Models? Surging Forward or Fighting Shy?

Latent variable models and interaction effects have both been common in the organizational sciences for some time. Methods for incorporating interactions into latent variable models have existed since at least Kenny and Judd, and a great many articles and books have developed these methods further. In the present article, we present an empirical review of the methods that organizational science investigators use to test their interaction hypotheses. We show that it is very common for investigators to use fully latent methods to test additive portions of their models, but to abandon such methods when testing the multiplicative portions of their models. By contrast, investigators whose models do not contain interactions tend to stick with fully latent methods throughout. As there is little rational basis for this pattern, it is likely due to continued discomfort regarding the proper application of existing fully latent methods. Thus, we end by offering R code that implements some of the more sophisticated fully latent approaches, and by offering a sequence of decisions that investigators can follow in order to choose the best analytic approach.

Dynamic patterns of marital conflict: Relations to trajectories of adolescent adjustment.

The deleterious effects of marital conflict on youth outcomes are well-documented in both cross-sectional and longitudinal studies. To date, longitudinal studies have focused on repeated measures of youths' outcomes and the temporal dynamics of marital conflict have largely been ignored. Marital conflict changes over time as contextual and relationship characteristics change, and these patterns of change may provide unique predictive power in accounting for differences in youth outcomes. This study provides a novel exploration of an old idea by focusing on dynamic patterns of marital conflict in predicting trajectories of adolescents' adjustment. All variables were measured at ages 16, 17, and 18 with 252 adolescents (53% female) enrolled in the longitudinal Family Stress and Youth Development Study. Latent growth curve models with latent variable interactions were used to determine whether marital conflict at age 16 (intercept), change over time in marital conflict (slope), and the intercept-slope interaction predicted change over time in adolescent internalizing and externalizing symptoms and levels of internalizing and externalizing symptoms at age 18. Youth exposed to high and increasing levels of marital conflict reported high and stable levels of internalizing and externalizing symptoms across adolescence. Adolescents exposed to low and decreasing levels of marital conflict had consistently fewer symptoms. Furthermore, exposure to initially low but increasing levels of marital conflict was associated with increases in problems across adolescence, which contrasted with findings for youth with initially high marital conflict exposure that decreased over time. Findings are discussed in relation to both conceptual and methodological advances. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Latent Variable Interactions With Ordered-Categorical Indicators: Comparisons of Unconstrained Product Indicator and Latent Moderated Structural Equations Approaches.

Methods to handle ordered-categorical indicators in latent variable interactions have been developed, yet they have not been widely applied. This article compares the performance of two popular latent variable interaction modeling approaches in handling ordered-categorical indicators: unconstrained product indicator (UPI) and latent moderated structural equations (LMS). We conducted a simulation study across sample sizes, indicators' distributions and category conditions. We also studied four strategies to create sets of product indicators for UPI. Results supported using a parceling strategy to create product indicators in the UPI approach or using the LMS approach when the categorical indicators are symmetrically distributed. We applied these models to study the interaction effect between third- to fifth-grade students' social skills improvement and teacher-student closeness on their state English language arts test scores.

Associations of Cumulative Family Risk With Academic Performance and Substance Involvement: Tests of Moderation by Child Reading Engagement

Background: Exposure to cumulative contextual risk within the family early in life increases children’s risk for substance involvement and related difficulties, including school failure, in adolescence and young adulthood. However, potential protective factors that buffer these risk associations are relatively untested, yet such tests are needed to improve existing preventive interventions for enhancing resilience among vulnerable children. Objectives: This study tested child reading engagement with parents at home as a moderator of cumulative family risk associations with adolescent substance use and academic performance as well as young adult substance abuse. Methods: Population register data as well as parent-report and adolescent-report data from 6,963 participants of the 1986 Northern Finland Birth Cohort study were analyzed via structural equation modeling with latent variable interactions. Results: Results showed that child reading engagement moderated the associations of cumulative family risk with both adolescent academic performance and young adult substance abuse, but not with adolescent substance use. The highest levels of academic performance were observed under conditions of low risk and high reading engagement. Interestingly, cumulative family risk had a small positive association with substance abuse when reading engagement was low and a negative association with the young adult outcome when reading engagement was high. Conclusions/Importance: Moderation tests revealed complex interaction forms that may have implications for both theory and family-based preventive interventions.

Pre-service teachers’ teaching-specific hopes and their motivational forces: The roles of efficacy beliefs and possible selves

Working with 725 pre-service teachers, this study examined the explanatory roles of efficacy beliefs, expected and feared teacher possible selves within a recently developed model of teaching-specific hopes. Latent-factor correlation analysis showed significant and selective relationships between the research variables. Subsequent structural equation modeling analysis revealed that the research variables were conceptually and practically discernible. Efficacy beliefs and loss of control were found to affect teaching-specific hopes directly. Latent variable interaction modeling analysis showed that interactions between efficacy beliefs and learning to teach positively predicted motivational force, and that those between efficacy beliefs and uncaring teacher negatively predicted motivational force.

Regulate yourself: Emotion regulation and protective behavioral strategies in substance use behaviors

Although research suggests links between emotion regulation strategies and substance use outcomes, little work has examined the relationship between specific strategies (i.e., reappraisal and suppression) and outcomes (i.e., alcohol and cannabis consumption and related problems). To date, no research has examined the association between emotion regulation strategies and protective behavioral strategies used while engaging in substance use. Thus, the current study examined these relations for females and males. Undergraduates (N = 643) completed an online battery of self-report measures. Using structural equation modeling, results indicated improved Emotion Regulation Questionnaire model fit after one item was removed. Reappraisal was negatively associated with alcohol binge frequency and related problems for females, though suppression was negatively related to these outcomes for males. Reappraisal was also negatively associated with cannabis-related problems for males only. Reappraisal was positively associated with all types of protective behavioral strategies use for females, whereas only alcohol-specific serious harm reduction and cannabis protective behavioral strategies were significant for males. Latent variable interactions between reappraisal and protective behavioral strategies were significant for past-month cannabis use and related problems for males and indicated protective behavioral strategies use was more protective against past-month use and cannabis-related problems for those high in reappraisal. Although replication is necessary, these preliminary findings suggest the link between emotion regulation strategies and substance use outcomes among college students is complex and future work may benefit from examining these relations from an emotion regulation flexibility perspective.