Parental attachment, parental control, and early development of alcohol use: A longitudinal study.

The authors explored the predictive influence of both parental attachment and parental control on early onset of alcohol consumption in adolescence by use of a longitudinal sample of 1,012 young adolescents. Whether the relationship between parental control and adolescents' drinking is moderated by parental attachment was also examined. Consistent with other studies, attachment and strict control were cross-sectionally related to adolescents' alcohol use at all 3 measurements. However, the longitudinal results of structural equation modeling analyses suggest that a good attachment relationship between parent and child does not prevent adolescents from drinking. In addition, strict control was related to lower engagement in alcohol use. Furthermore, with regard to the moderating effect, parental attachment did not moderate longitudinally the association between parental control and an early development of alcohol use. Implications for further research are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Missing not at random models for latent growth curve analyses.

The past decade has seen a noticeable shift in missing data handling techniques that assume a missing at random (MAR) mechanism, where the propensity for missing data on an outcome is related to other analysis variables. Although MAR is often reasonable, there are situations where this assumption is unlikely to hold, leading to biased parameter estimates. One such example is a longitudinal study of substance use where participants with the highest frequency of use also have the highest likelihood of attrition, even after controlling for other correlates of missingness. There is a large body of literature on missing not at random (MNAR) analysis models for longitudinal data, particularly in the field of biostatistics. Because these methods allow for a relationship between the outcome variable and the propensity for missing data, they require a weaker assumption about the missing data mechanism. This article describes 2 classic MNAR modeling approaches for longitudinal data: the selection model and the pattern mixture model. To date, these models have been slow to migrate to the social sciences, in part because they required complicated custom computer programs. These models are now quite easy to estimate in popular structural equation modeling programs, particularly Mplus. The purpose of this article is to describe these MNAR modeling frameworks and to illustrate their application on a real data set. Despite their potential advantages, MNAR-based analyses are not without problems and also rely on untestable assumptions. This article offers practical advice for implementing and choosing among different longitudinal models. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

A longitudinal model of social contact, social support, depression, and alcohol use.

The longitudinal relations among contact with one's social network (social contact), perceived social support, depression, and alcohol use were examined. An integrative model was developed from affect regulation theory and theories of social support and dysfunctional drinking. Data were obtained from a random sample of 1, 192 adults. The 3-wave panel model was tested using structural equation modeling analysis. Results revealed that (a) social contact was positively related to perceived social support; (b) perceived social support was, in turn, negatively related to depression; and (c) depression was, in turn, positively related to alcohol use for 1 of 2 longitudinal lags. There was partial support for the feedback hypothesis that increased alcohol use leads to decreased contact with family and friends. Although the results generally supported the authors' hypotheses, the significant coefficients in the model were generally small in size. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analyzing longitudinal data with multilevel models: An example with individuals living with lower extremity intra-articular fractures.

Objective: The use and quality of longitudinal research designs has increased over the past 2 decades, and new approaches for analyzing longitudinal data, including multilevel modeling (MLM) and latent growth modeling (LGM), have been developed. The purpose of this article is to demonstrate the use of MLM and its advantages in analyzing longitudinal data. Research Method: Data from a sample of individuals with intra-articular fractures of the lower extremity from the University of Alabama at Birmingham's Injury Control Research Center are analyzed using both SAS PROC MIXED and SPSS MIXED. Results: The authors begin their presentation with a discussion of data preparation for MLM analyses. The authors then provide example analyses of different growth models, including a simple linear growth model and a model with a time-invariant covariate, with interpretation for all the parameters in the models. Implications: More complicated growth models with different between- and within-individual covariance structures and nonlinear models are discussed. Finally, information related to MLM analysis, such as online resources, is provided at the end of the article. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Measurement invariance in longitudinal clinical research assuming change from development and intervention.

Valid and reliable measures of psychological and behavioral constructs are critical to clinical research, particularly longitudinal treatment research, in which multiple groups are compared over time for possible changes within and between constructs as a result of intervention or development. Structural equation modeling (SEM) analysis is a class of statistical procedures that can be used to test multiple hypotheses about these relationships simultaneously while controlling for measurement error. The procedures have been applied primarily to testing between-construct relationships in nonexperimental studies, with relatively little emphasis on establishing whether measures are sufficiently invariant across groups and across time to permit these tests. This article uses an empirical example of a longitudinal experimental prevention study with 2 groups to illustrate the use of SEM, first, to systematically test measurement invariance across groups at each wave of measurement, and second, after establishing measurement invariance, to test structural invariance longitudinally. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to the Special Section on Applied Longitudinal Methods in Aging Research.

This article introduces articles that appear in the special section on applied longitudinal methods in aging research. These articles apply quantitative statistical techniques such as multilevel modeling and structural equation models to the analysis of longitudinal data. They exemplify how applications of these techniques can advance scientific research on the effects of aging on psychological constructs. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Using covariance structure analysis to detect correlates and predictors of individual change over time.

Recently, methodologists have shown how 2 disparate conceptual arenas (individual growth modeling and covariance structure analysis) can be integrated. The integration brings the flexibility of covariance analysis to bear on the investigation of systematic interindividual differences in change and provides another powerful data-analytic tool for answering questions about the relationship between individual true change and potential predictors of that change. The individual growth modeling framework uses a pair of hierarchical statistical models to represent (1) within-person true status as a function of time and (2) between-person differences in true change as a function of predictors. This article explains how these models can be reformatted to correspond, respectively, to the measurement and structural components of the general LISREL model with mean structures and illustrates, by means of worked example, how the new method can be applied to a sample of longitudinal panel data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Family functioning predicts outcomes for veterans in treatment for chronic posttraumatic stress disorder.

A longitudinal framework was used to examine the competing hypotheses of (a) whether family functioning predicts changes in posttraumatic stress disorder (PTSD) symptoms or (b) whether PTSD symptoms predict changes in family functioning. Veterans (N = 311) admitted to a treatment program completed a series of questionnaires at 3 time points: at intake, from intake to completion of a treatment program, and at the 6-month follow-up. Alcohol use and general mental health symptoms were also measured at intake. A cross-lagged panel model using structural equation modeling analyses indicated that family functioning was a moderate predictor of PTSD symptoms at posttreatment and at the 6-month follow-up. PTSD was not a significant predictor of family functioning across time and alcohol use, and general mental health symptoms did not affect the overall findings. Further analyses of PTSD symptom clusters indicated that the avoidance symptom cluster was most strongly related to family functioning. Targeting family relationships for treatment may be important in the future for veterans with PTSD. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Parental management of adolescent peer relationships in context: The role of parenting style.

Three hundred 9th-graders and their best friends participated in this short-term longitudinal study. Confirmatory factor analysis of the Parental Management of Peers Inventory (N. Mounts, 2000) suggested that the 4-factor structure provided a good fit to the data. Significant differences in adolescents' perceptions of parental management of peers occurred across 4 parenting style groups. Structural equation modeling was used to examine the relation among 5 aspects of parental management of peers and adolescents' Time 1 drug use, friends' Time 1 drug use, and adolescents' Time 2 drug use. The parental management styles of monitoring, guiding, prohibiting, and supporting all had significant paths in the model, whereas neutrality was not significant. Multiple group comparisons were used to examine whether parenting style moderates the relation between parental management of peers and the drug use outcomes. Parenting style functioned as a moderator for 7 of the paths in the model. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Ecological predictors of substance use in middle school students.

The current study examined important predictors of substance use during early adolescence. The authors hypothesized that adolescents' relationships with key adults (i.e., teachers and parents) influence their choices to use substances indirectly through links with their decisions regarding peer groups. A total of 461 middle school students from an affluent suburban community completed self-report measures of authoritative parenting, perceived social support from teachers, affiliation with rule-breaking and substance-using peers, and frequency of alcohol, cigarette, and drug use. Results of structural equation modeling supported the hypothesized model. Authoritative parenting and teacher support accounted for 31% of the variance in affiliation with deviant peers which, in turn, accounted for 27% of the variance in adolescent substance use; direct paths from parenting and teacher support to substance use were not indicated. Implications for school psychologists' involvement in substance use prevention and intervention are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Formulating clinical research hypotheses as structural equation models: A conceptual overview.

Structural equation modeling is a comprehensive, flexible approach to research design and data analysis. Although in recent years there has been phenomenal growth in the literature on technical aspects of structural equation modeling, relatively little attention has been devoted to conceiving research hypotheses as structural equation models. The aim of this article is to provide a conceptual overview of clinical research hypotheses that invite evaluation as structural equation models. Particular attention is devoted to hypotheses that are not adequately evaluated using traditional statistical models. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Individuation, peers, and adolescent alcohol use: A latent growth analysis.

The study used latent growth modeling to investigate longitudinal relationships between individuation, peer alcohol use, and adolescent alcohol use among African American, Mexican American, and non-Hispanic White adolescents (N=6,048) from 7th, 8th, and 9th grades over a 3-year period. Initial levels of peer alcohol use were significantly related to changes in adolescents' alcohol use, whereas initial adolescent alcohol use also significantly related to changes in peers' alcohol use, suggesting a bidirectional relationship. Higher levels of intergenerational individuation were related to smaller increases in adolescent alcohol use and higher levels of separation were related to larger increases in youth drinking. The findings were similar across ethnic groups. Implications for development of prevention and intervention programs are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A comparison of two latent variable causal models for adolescent drug use.

Compared the competing simplex (involvement) and common factor models for youthful drug use using causal modeling with latent variables methods with 1,634 students in Grades 7–9. Latent variables of alcohol, marihuana, and other illicit drug use were confirmed and causally interconnected in a set of states. The confirmatory factor and the simplex stage models were found to be acceptable representations of the observed data according to both statistical and psychometric criteria. Results are discussed in terms of their implications for theories of emerging life-styles including drug use, methodology, and policy about psychoactive substances. (44 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mother-child relationship quality and effective discipline as mediators of the 6-year effects of the New Beginnings Program for children from divorced families.

This study examines whether program effects on mother-child relationship quality and effective discipline mediated the 6-year longitudinal effects of the New Beginnings Program (NBP) to improve mental health and competence outcomes in 218 adolescents from divorced families in a randomized experimental trial. The NBP is a theory-based and parenting-focused preventive intervention to help children adjust to divorce, and it has previously shown significant main and/or Program × Baseline Risk interaction effects to reduce adolescents' mental health and social adaptation problems and to promote competence. Mediation analyses were conducted using single- and two-group (high and low baseline risk) structural equation modeling. A multiple-methods and multiple-informants approach was used to assess the putative mediators and adolescents' outcomes. Results indicated that program-induced improvement in maternal effective discipline at posttest mediated the intervention effect on adolescents' GPA at the 6-year follow-up. Moreover, program-induced improvement in mother-child relationship quality mediated the intervention effect on adolescents' mental health problems for those with high baseline risk for maladjustment. The discussion focuses on the implications of the mediation findings for advancing the developmental theories that informed the design of the NBP and the implications for implementation of the NBP in community settings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Role of family and peers in the development of prototypes associated with substance use.

Prior research and theory suggest that adolescents often experiment with substances to acquire desired social images. However, little research has addressed the developmental precursors leading to favorable evaluation of substance users. This study tested a model of parental and peer influence on adolescent prototypes using a longitudinal data set of 463 rural adolescents. For both drinking and smoking, positive prototypes of substance users were best predicted by peer affiliations. Adolescents who affiliated with peers who practiced and encouraged substance use developed more positive prototypes of people who drink and smoke. These social images, in turn, predicted subsequent use of alcohol and cigarettes. In contrast to peers, parents had little direct influence on prototypes but did indirectly affect images through the adolescents' choice of peers. Unexpectedly, there was evidence of a negative modeling effect of parental substance use, such that parental smoking predicted more negative prototypes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Effects of parents' experiential avoidance and PTSD on adolescent disaster-related posttraumatic stress symptomatology.

Despite the importance of family context to adolescents' reactions following disaster, little research has examined the role of parents' functioning on adolescents' disaster-related posttraumatic stress disorder (PTSD) symptoms. Using data from 288 adolescents (ages 12 to 19 years) and 288 parents exposed to a series of severe tornadoes in a rural Midwestern community, this study tested a conceptual model of the interrelationships between individual and parental risk factors on adolescents' disaster-related PTSD symptoms using structural equation modeling. Results showed that the psychological process of experiential avoidance mediated the relationship between family disaster exposure and PTSD for both adolescents and their parents. Parents' PTSD symptoms independently predicted adolescents' PTSD symptoms. Further, parents' postdisaster functioning amplified the effects of adolescent experiential avoidance on adolescents' disaster-related PTSD symptoms. Findings highlight the importance of family context in understanding adolescents' postdisaster reactions. Clinical implications are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

A cautionary note on measurement error corrections in structural equation models.

It is commonly thought that structural equation modeling corrects estimated relationships among latent variables for the biasing effects of measurement error. The purpose of this article is to review the manner in which structural equation models control for measurement error and to demonstrate the conditions in which structural equation models do and do not correct for unreliability. Generalizability theory is used to demonstrate that there are multiple sources of error in most measurement systems and that applications of structural equation modeling rarely account for more than a single source of error. As a result, the parameter estimates in a structural equation model may be severely biased by unassessed sources of measurement error. Recommendations for modeling multiple sources of error in structural equation models are provided. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Testing Mediational Models With Longitudinal Data: Questions and Tips in the Use of Structural Equation Modeling.

R. M. Baron and D. A. Kenny (1986; see record 1987-13085-001) provided clarion conceptual and methodological guidelines for testing mediational models with cross-sectional data. Graduating from cross-sectional to longitudinal designs enables researchers to make more rigorous inferences about the causal relations implied by such models. In this transition, misconceptions and erroneous assumptions are the norm. First, we describe some of the questions that arise (and misconceptions that sometimes emerge) in longitudinal tests of mediational models. We also provide a collection of tips for structural equation modeling (SEM) of mediational processes. Finally, we suggest a series of 5 steps when using SEM to test mediational processes in longitudinal designs: testing the measurement model, testing for added components, testing for omitted paths, testing the stationarity assumption, and estimating the mediational effects. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The study of intraindividual differences by means of dynamic factor models: Rationale, implementation, and interpretation.

Study of reactive elements of behavior such as those responsible for mood disorder, arousal, and impulsivity often requires use of statistical models that involve time-bound relationships. P. C. Molenaar (see record 1985-27072-001) proposed the dynamic factor model for the analysis of multivariate repeated data. Conducting dynamic factor analyses using traditional structural equation programs is difficult because specification of such models involves extensive programming data manipulation and hand calculation to conduct such a time series analysis. This article outlines the dynamic factor model in terms of path diagrams and provides 3 SAS? macros that make specifying and conducting analyses easy. Problems of nonconvergence, improper solutions, and appropriate cutoff values for incremental fit indices are explored by means of a small Monte Carlo study. An example of physiological monitoring illustrates application of the model and use of the macros. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Family rituals in New Zealand families: Links to family cohesion and adolescents' well-being.

This research examined the longitudinal links between perceptions of family rituals, family cohesion, and adolescents' well-being in 713 adolescent–parent/caregiver dyads in New Zealand. Parents (86% mothers) assessed family ritual meaning and family cohesion, and adolescents (10 to 16 years old at Time 1) reported on family cohesion and well-being at two times of measurement with a 1-year interval. Structural equation modeling (SEM) was used to assess stability coefficients, cross-lagged effects, and to test a multistep mediation model. Results showed longitudinal bidirectional effects between perceptions of family ritual meaning and family cohesion (for parents), and between perceptions of family cohesion from parents/caregivers and adolescents. In addition, family ritual meaning was found to be linked to adolescents' well-being indirectly via parents' and adolescents' family cohesion. Results support and expand previous research on the direct and indirect effects of family rituals in family and individual positive outcomes. (PsycINFO Database Record (c) 2011 APA, all rights reserved)