Executive function in older adults: A structural equation modeling approach.

Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to study the organization of executive functions in older adults. The four primary goals were to examine (a) whether executive functions were supported by one versus multiple underlying factors, (b) which underlying skill(s) predicted performance on complex executive function tasks, (c) whether performance on analogous verbal and nonverbal tasks was supported by separable underlying skills, and (d) how patterns of performance generally compared with those of young adults. A sample of 100 older adults completed 10 tasks, each designed to engage one of three control processes: mental set shifting (Shifting), information updating or monitoring (Updating), and inhibition of prepotent responses (Inhibition). CFA identified robust Shifting and Updating factors, but the Inhibition factor failed to emerge, and there was no evidence for verbal and nonverbal factors. SEM showed that Updating was the best predictor of performance on each of the complex tasks the authors assessed (the Tower of Hanoi and the Wisconsin Card Sort). Results are discussed in terms of insight for theories of cognitive aging and executive function. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural equation modeling with interchangeable dyads.

Structural equation modeling (SEM) can be adapted in a relatively straightforward fashion to analyze data from interchangeable dyads (i.e., dyads in which the 2 members cannot be differentiated). The authors describe a general strategy for SEM model estimation, comparison, and fit assessment that can be used with either dyad-level or pairwise (double-entered) dyadic data. They present applications illustrating this approach with the actor-partner interdependence model, confirmatory factor analysis, and latent growth curve analysis. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Analyzing data from experimental studies: A latent variable structural equation modeling approach.

This article illustrates the use of structural equation modeling (SEM) procedures with latent variables to analyze data from experimental studies. These procedures allow the researcher to remove the biasing effects of random and correlated measurement error on the outcomes of the experiment and to examine processes that may account for changes in the outcome variables that are observed. Analyses of data from a Project Family study, an experimental intervention project with rural families that strives to improve parenting skills, are presented to illustrate the use of these modeling procedures. Issues that arise in applying SEM procedures, such as sample size and distributional characteristics of the measures, are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mechanisms linking socioeconomic status to smoking cessation: A structural equation modeling approach.

Objective: Although there has been a socioeconomic gradient in smoking prevalence, cessation, and disease burden for decades, these disparities have become even more pronounced over time. The aim of the current study was to develop and test a conceptual model of the mechanisms linking socioeconomic status (SES) to smoking cessation. Design: The conceptual model was evaluated using a latent variable modeling approach in a sample of 424 smokers seeking treatment (34% African American; 33% Latino; 33% White). Hypothesized mechanisms included social support, neighborhood disadvantage, negative affect/stress, agency, and craving. Main Outcome Measure: The primary outcome was Week 4 smoking status. Results: As was hypothesized, SES had significant direct and indirect effects on cessation. Specifically, neighborhood disadvantage, social support, negative affect/stress, and agency mediated the relation between SES and smoking cessation. A multiple group analysis indicated that the model was a good fit across racial/ethnic groups. Conclusion: The present study yielded one of the more comprehensive models illuminating the specific mechanisms that link SES and smoking cessation. Policy, community, and individual-level interventions that target low SES smokers and address the specific pathways identified in the current model could potentially attenuate the impact of SES on cessation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Introduction to the special section: Structural equation modeling in clinical research.

Clinical research hypotheses are becoming increasingly more complex and specific. As a result, clinical research studies often include multiple independent, intervening, and dependent variables in a single study. Nevertheless, a sampling of studies from 3 decades of research published in the Journal of Consulting and Clinical Psychology reveals that the statistical models adopted by clinical researchers have failed to keep pace with the increasing complexity and specificity of hypotheses and research designs. This article introduces a special section on structural equation modeling, a statistical model well suited for complex and specific hypothesis tests in clinical research studies that include many variables. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A structural equation modeling approach to the multiple memory systems question.

Used linear structural equation modeling to test 2 models of declarative memory. A unitary model was compared with the semantic-episodic theory proposed by E. Tulving (e.g., 1972, 1983). The data consisted of performance scores of 300 Ss on 14 cognitive tests. The results of 2 sets of analyses suggest rejection of the unitary model but not the 2-factor model. Moreover, nested comparisons of the models revealed that the 2-factor model provided a significantly better fit to data than did the unitary model. Results support a division of declarative memory into memory for episodic information and memory for facts. This finding is discussed in terms of (1) different underlying memory systems mediating performance on semantic and episodic tests and (2) differences in the retrieval strategies that are required for accessing semantic and episodic information. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural equation modeling: Reply to Marsh et al. (1994).

In our previous article (B. S. Randhawa et al; see record 1993-23567-001), we concluded that (1) the endogenous latent variable (self-efficacy) mediated the exogenous latent variable (attitude) and the endogenous latent variable (mathematics achievement) and that (2) self-efficacy and attitude were more strongly related to achievement for boys than for girls. H. W. Marsh et al (see record 1995-03503-001) claimed that we inappropriately applied the structure equation modeling and consequently our conclusions are unsubstantiated. We defend our analysis and conclusions. We show that a philosophically different perspective in their reanalysis of the covariance matrices and the fact that their input data were derived from our reported truncated summary results may have been the basis for the differences in their results and conclusions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mediation in dyadic data at the level of the dyads: A structural equation modeling approach.

An extended version of the Common Fate Model (CFM) is presented to estimate and test mediation in dyadic data. The model can be used for distinguishable dyad members (e.g., heterosexual couples) or indistinguishable dyad members (e.g., homosexual couples) if (a) the variables measure characteristics of the dyadic relationship or shared external influences that affect both partners; if (b) the causal associations between the variables should be analyzed at the dyadic level; and if (c) the measured variables are reliable indicators of the latent variables. To assess mediation using Structural Equation Modeling, a general three-step procedure is suggested. The first is a selection of a good fitting model, the second a test of the direct effects, and the third a test of the mediating effect by means of bootstrapping. The application of the model along with the procedure for assessing mediation is illustrated using data from 184 couples on marital problems, communication, and marital quality. Differences with the Actor-Partner Interdependence Model and the analysis of longitudinal mediation by using the CFM are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Perceived coping as a mediator between attachment and psychological distress: A structural equation modeling approach.

This study examined perceived coping (perceived problem-solving ability and progress in coping with problems) as a mediator between adult attachment (anxiety and avoidance) and psychological distress (depression, hopelessness, anxiety, anger, and interpersonal problems). Survey data from 515 undergraduate students were analyzed using structural equation modeling. Results indicated that perceived coping fully mediated the relationship between attachment anxiety and psychological distress and partially mediated the relationship between attachment avoidance and psychological distress. These findings suggest not only that it is important to consider attachment anxiety or avoidance in understanding distress but also that perceived coping plays an important role in these relationships. Implications for these more complex relations are discussed for both counseling interventions and further research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Social exchange, equity, and commitment: Structural equation modeling of dating relationships.

Used structural equation modeling in 2 studies to evaluate the social exchange (SE) hypothesis, which states that relationship commitment results from satisfaction with the relationship, paired with the limited availability of desirable alternative relationships. College students in intimate relationships completed questionnaire measures of commitment, satisfaction, perceptions of alternatives, and inequity. The initial study, with 238 Ss, supported the SE model but also suggested that perceptions of alternatives involved separating the field of desirable alternatives from the field of available alternatives. Study 2, with 423 Ss, was a replication of Study 1. It also ruled out gender differences, and tested and supported an expanded SE model, which included the construct inequity as an additional intrinsic factor that had substantial indirect influences on relationship commitment as mediated through its effect on satisfaction. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Fitting data to model: Structural equation modeling diagnosis using two scatter plots.

This article introduces two simple scatter plots for model diagnosis in structural equation modeling. One plot contrasts a residual-based M-distance of the structural model with the M-distance for the factor score. It contains information on outliers, good leverage observations, bad leverage observations, and normal cases. The other plot contrasts the residual-based M-distance with the quantile of a chi distribution. It allows the researcher to visually identify clusters of potential outliers. The article further studies the effect of the potential outliers on the overall model evaluation when they are removed according to the order of the clusters exhibited in the plot. Suggestions are provided on determining the outlier status of outstanding cases in real data analysis. Recommendations are also made on the choice of robust methods and maximum likelihood following outlier removal. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural priming: A critical review.

Repetition is a central phenomenon of behavior, and researchers have made extensive use of it to illuminate psychological functioning. In the language sciences, a ubiquitous form of such repetition is structural priming, a tendency to repeat or better process a current sentence because of its structural similarity to a previously experienced ("prime") sentence (J. K. Bock, 1986). The recent explosion of research in structural priming has made it the dominant means of investigating the processes involved in the production (and increasingly, comprehension) of complex expressions such as sentences. This review considers its implications for the representation of syntax and the mechanisms of production and comprehension and their relationship. It then addresses the potential functions of structural priming, before turning to its implications for first language acquisition, bilingualism, and aphasia. The authors close with theoretical and empirical recommendations for future investigations. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural equation modeling with longitudinal data: Strategies for examining group differences and reciprocal relationships.

This article describes the use of structural equation modeling with latent variables to examine group differences and test competing models about cause–effect relationships in passive longitudinal designs. This approach is compared with several other statistical methods including analysis of cross-lagged panel correlations, regression analysis, and path analysis. The mechanics and advantages of structural equation modeling are illustrated using an example based on a 3-wave longitudinal study of adolescents' alcohol use. Within this example, the generalizability of the measurement model and structural model are assessed across gender and time, and competing models about the causes and consequences of adolescents' alcohol use are tested. The article concludes with a discussion of some of the strengths and limitations of using structural equation modeling with longitudinal data. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Therapeutic videotape and film modeling: A review.

Reviews research involving the use of videotape and film modeling in clinical and analog settings. Most of the research has been on phobias, test anxiety, dental and medical stress, and interpersonal skills. The relevance of this research to modeling theory and critical methodological issues is also discussed. The need for improved methodology and the application of videotape and film modeling in more clinical populations is emphasized. (74 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural equation modeling of multitrait-multimethod data: Different models for different types of methods.

The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods used) should guide the choice of the statistical model to analyze the data. In this respect, the authors distinguish between (a) interchangeable methods, (b) structurally different methods, and (c) the combination of both kinds of methods. The authors present an appropriate model for each type of method. All models allow separating measurement error from trait influences and trait-specific method effects. With respect to interchangeable methods, a multilevel confirmatory factor model is presented. For structurally different methods, the correlated trait-correlated (method-1) model is recommended. Finally, the authors demonstrate how to appropriately analyze data from MTMM designs that simultaneously use interchangeable and structurally different methods. All models are applied to empirical data to illustrate their proper use. Some implications and guidelines for modeling MTMM data are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Latent variable interaction and quadratic effect estimation: A two-step technique using structural equation analysis.

The author proposes an alternative estimation technique for latent variable interactions and quadratics. Available techniques for specifying these variables in structural equation models require adding variables or constraint equations that can produce specification tedium and errors or estimation difficulties. The proposed technique avoids these difficulties and may be useful for EQS, LISREL 7, and LISREL 8 users. First, measurement parameters for indicator loadings and errors of linear latent variables are estimated in a measurement model that excludes the interaction and quadratic variables. Next, these estimates are used to calculate values for the indicator loadings and error variances of the interaction and quadratic latent variables. Then, these calculated values are specified as constants in the structural model containing the interaction and quadratic variables. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A generalized estimating equation approach for modeling random length binary vector data

A common measure in clinical trials and epidemiologic studies is the number of events such as seizures, hospitalizations, or bouts of disease. Frequently, a binary measure of severity for each event is available but is not incorporated in the analysis. This paper proposes methodology for jointly modeling the number of events and the vector of correlated binary severity measures. Our formulation exploits the notion that a given covariate may affect both outcomes in a similar way. We functionally link the regression parameters for the counts and binary means and discuss a generalized estimating equation (GEE) approach for parameter estimation. We discuss conditions under which the proposed joint modeling approach provides marked gains in efficiency relative to the common procedure of simply modeling the counts, and we illustrate the methodology with epilepsy clinical trial data.     

Peer review: A private practice model.

The Peninsula Hospital Community Mental Health Center in California, in collaboration with community private practitioners, instituted a peer review plan to meet fiscal problems while permitting quality patient care. The present paper describes the plan and the functioning of the peer review committee. There were initial objections to the plan by most of the private practicing professionals concerned. The attitudes of 76 practitioners, as well as those of 19 peer reviewers, were assessed in questionnaires 3 yrs after the start of the peer review plan. Results of the questionnaires are discussed. (5 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Structural equation modeling of relationships among developmental skills and writing skills in primary- and intermediate-grade writers.

Used multiple-group structural equation modeling to analyze structural relationships between latent factors underlying writing-related developmental skills and component writing skills in Grades 1–6. For handwriting, both motor skills and orthographic coding contributed to the model fit, but only the path from orthographic coding was significant at all grade levels. For spelling, only the path from orthographic coding was significant in the primary grades, but both that path and the path from phonological coding were significant in the intermediate grades. For compositional quality, both reading and oral language contributed in the primary grades, but the model was unclear in the intermediate grades because of high covariance between those factors. Theoretical and educational implications of the findings are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Common method biases in behavioral research: A critical review of the literature and recommended remedies.

Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)