Fitting ACE Structural Equation Models to Case-Control Family Data

Investigators interested in whether a disease aggregates in families often collect case-control family data, which consist of disease status and covariate information for families selected via case or control probands. Here, we focus on the use of case-control family data to investigate the relative contributions to the disease of additive genetic effects (A), shared family environment (C), and unique environment (E). To this end, we describe a ACE model for binary family data and then introduce an approach to fitting the model to case-control family data. The structural equation model, which has been described previously, combines a general-family extension of the classic ACE twin model with a (possibly covariate-specific) liability-threshold model for binary outcomes. Our likelihood-based approach to fitting involves conditioning on the proband’s disease status, as well as setting prevalence equal to a pre-specified value that can be estimated from the data themselves if necessary. Simulation experiments suggest that our approach to fitting yields approximately unbiased estimates of the A, C, and E variance components, provided that certain commonly-made assumptions hold. These assumptions include: the usual assumptions for the classic ACE and liability-threshold models; assumptions about shared family environment for relative pairs; and assumptions about the case-control family sampling, including single ascertainment. When our approach is used to fit the ACE model to Austrian case-control family data on depression, the resulting estimate of heritability is very similar to those from previous analyses of twin data.

The Relationship Between Sociosexuality and Aspects of Body Image in Men and Women: A Structural Equation Modeling Approach

The present study investigated the association between individual differences in sociosexual orientation and four aspects of body image in 156 male and 136 female students. While men were characterized by a less restricted sociosexual orientation, higher self-perceived physical attractiveness, and more pronounced self-rated physical assertiveness, women placed more emphasis on accentuation of body presentation. Structural equation modeling revealed significant positive relationships between sociosexual attitudes and physical attractiveness and accentuation of body presentation as well as between sociosexual behavior and physical attractiveness for the total sample. When introducing sex as a grouping variable, the attitudinal and behavioral components of sociosexuality were reliably related to both physical attractiveness and accentuation of body presentation as two aspects of body image in men, but not in women. Furthermore, our findings suggest that accentuation of body presentation represents a goal-directed behavior in men to increase the likelihood of having uncommitted sex but serves additional functions widely unrelated to unrestrictive sociosexual behavior in women.

Prospective memory, executive functions and metacognitive control: An empirical approach to their structural interrelations in young elementary school children

Introduction Prospective memory (PM), the ability to remember to perform intended activities in the future (Kliegel & Jäger, 2007), is crucial to succeed in everyday life. PM seems to improve gradually over the childhood years (Zimmermann & Meier, 2006), but yet little is known about PM competences in young school children in general, and even less is known about factors influencing its development. Currently, a number of studies suggest that executive functions (EF) are potentially influencing processes (Ford, Driscoll, Shum & Macaulay, 2012; Mahy & Moses, 2011). Additionally, metacognitive processes (MC: monitoring and control) are assumed to be involved while optimizing one’s performance (Krebs & Roebers, 2010; 2012; Roebers, Schmid, & Roderer, 2009). Yet, the relations between PM, EF and MC remain relatively unspecified. We intend to empirically examine the structural relations between these constructs. Method A cross-sectional study including 119 2nd graders (mage = 95.03, sdage = 4.82) will be presented. Participants (n = 68 girls) completed three EF tasks (stroop, updating, shifting), a computerised event-based PM task and a MC spelling task. The latent variables PM, EF and MC that were represented by manifest variables deriving from the conducted tasks, were interrelated by structural equation modelling. Results Analyses revealed clear associations between the three cognitive constructs PM, EF and MC (rpm-EF = .45, rpm-MC = .23, ref-MC = .20). A three factor model, as opposed to one or two factor models, appeared to fit excellently to the data (chi2(17, 119) = 18.86, p = .34, remsea = .030, cfi = .990, tli = .978). Discussion The results indicate that already in young elementary school children, PM, EF and MC are empirically well distinguishable, but nevertheless substantially interrelated. PM and EF seem to share a substantial amount of variance while for MC, more unique processes may be assumed.

Structural equation modeling of the medical outcome study: Short Form 36 (SF-36)

The factorial validity of the SF-36 was evaluated using confirmatory factor analysis (CFA) methods, structural equation modeling (SEM), and multigroup structural equation modeling (MSEM). First, the measurement and structural model of the hypothesized SF-36 was explicated. Second, the model was tested for the validity of a second-order factorial structure, upon evidence of model misfit, determined the best-fitting model, and tested the validity of the best-fitting model on a second random sample from the same population. Third, the best-fitting model was tested for invariance of the factorial structure across race, age, and educational subgroups using MSEM.^ The findings support the second-order factorial structure of the SF-36 as proposed by Ware and Sherbourne (1992). However, the results suggest that: (a) Mental Health and Physical Health covary; (b) general mental health cross-loads onto Physical Health; (c) general health perception loads onto Mental Health instead of Physical Health; (d) many of the error terms are correlated; and (e) the physical function scale is not reliable across these two samples. This hierarchical factor pattern was replicated across both samples of health care workers, suggesting that the post hoc model fitting was not data specific. Subgroup analysis suggests that the physical function scale is not reliable across the "age" or "education" subgroups and that the general mental health scale path from Mental Health is not reliable across the "white/nonwhite" or "education" subgroups.^ The importance of this study is in the use of SEM and MSEM in evaluating sample data from the use of the SF-36. These methods are uniquely suited to the analysis of latent variable structures and are widely used in other fields. The use of latent variable models for self reported outcome measures has become widespread, and should now be applied to medical outcomes research. Invariance testing is superior to mean scores or summary scores when evaluating differences between groups. From a practical, as well as, psychometric perspective, it seems imperative that construct validity research related to the SF-36 establish whether this same hierarchical structure and invariance holds for other populations.^ This project is presented as three articles to be submitted for publication. ^

A structural model of cognitive-motivational variables as explanatory factors of academic achievement in Spanish Language and Mathematics

In recent years, several explanatory models have been developed which attempt to analyse the predictive worth of various factors in relation to academic achievement, as well as the direct and indirect effects that they produce. The aim of this study was to examine a structural model incorporating various cognitive and motivational variables which influence student achievement in the two basic core skills in the Spanish curriculum: Spanish Language and Mathematics. These variables included differential aptitudes, specific self-concept, goal orientations, effort and learning strategies. The sample comprised 341 Spanish students in their first year of Compulsory Secondary Education. Various tests and questionnaires were used to assess each student, and Structural Equation Modelling (SEM) was employed to study the relationships in the initial model. The proposed model obtained a satisfactory fit for the two subjects studied, and all the relationships hypothesised were significant. The variable with the most explanatory power regarding academic achievement was mathematical and verbal aptitude. Also notable was the direct influence of specific self-concept on achievement, goal-orientation and effort, as was the mediatory effect that effort and learning strategies had between academic goals and final achievement.

Functional recycling of C2 domains throughout evolution: A comparative study of synaptotagmin, protein kinase C and phospholipase C by sequence, structural and modelling approaches

The C2 domain is one of the most frequent and widely distributed calcium-binding motifs. Its structure comprises an eight-stranded beta-sandwich with two structural types as if the result of a circular permutation. Combining sequence, structural and modelling information, we have explored, at different levels of granularity, the functional characteristics of several families of C2 domains. At the coarsest level,the similarity correlates with key structural determinants of the C2 domain fold and, at the finest level, with the domain architecture of the proteins containing them, highlighting the functional diversity between the various subfamilies. The functional diversity appears as different conserved surface patches throughout this common fold. In some cases, these patches are related to substrate-binding sites whereas in others they correspond to interfaces of presumably permanent interaction between other domains within the same polypeptide chain. For those related to substrate-binding sites, the predictions overlap with biochemical data in addition to providing some novel observations. For those acting as protein-protein interfaces' our modelling analysis suggests that slight variations between families are a result of not only complementary adaptations in the interfaces involved but also different domain architecture. In the light of the sequence and structural genomic projects, the work presented here shows that modelling approaches along with careful sub-typing of protein families will be a powerful combination for a broader coverage in proteomics. (C) 2003 Elsevier Ltd. All rights reserved.

Functional-structural plant modelling using a combination of architectural analysis, L-systems and a canonical model of function

This paper presents a new method for producing a functional-structural plant model that simulates response to different growth conditions, yet does not require detailed knowledge of underlying physiology. The example used to present this method is the modelling of the mountain birch tree. This new functional-structural modelling approach is based on linking an L-system representation of the dynamic structure of the plant with a canonical mathematical model of plant function. Growth indicated by the canonical model is allocated to the structural model according to probabilistic growth rules, such as rules for the placement and length of new shoots, which were derived from an analysis of architectural data. The main advantage of the approach is that it is relatively simple compared to the prevalent process-based functional-structural plant models and does not require a detailed understanding of underlying physiological processes, yet it is able to capture important aspects of plant function and adaptability, unlike simple empirical models. This approach, combining canonical modelling, architectural analysis and L-systems, thus fills the important role of providing an intermediate level of abstraction between the two extremes of deeply mechanistic process-based modelling and purely empirical modelling. We also investigated the relative importance of various aspects of this integrated modelling approach by analysing the sensitivity of the standard birch model to a number of variations in its parameters, functions and algorithms. The results show that using light as the sole factor determining the structural location of new growth gives satisfactory results. Including the influence of additional regulating factors made little difference to global characteristics of the emergent architecture. Changing the form of the probability functions and using alternative methods for choosing the sites of new growth also had little effect. (c) 2004 Elsevier B.V. All rights reserved.

Using structural equation modeling to assess two theoretical models that explain dropout

This study evaluated the relative fit of both Finn's (1989) Participation-Identification and Wehlage, Rutter, Smith, Lesko and Fernandez's (1989) School Membership models of high school completion to a sample of 4,597 eighth graders taken from the National Educational Longitudinal Study of 1988, (NELS:88), utilizing structural equation modeling techniques. This study found support for the importance of educational engagement as a factor in understanding academic achievement. The Participation-Identification model was particularly well fitting when applied to the sample of high school completers, dropouts (both overall and White dropouts) and African-American students. This study also confirmed the contribution of school environmental factors (i.e., size, diversity of economic and ethnic status among students) and family resources (i.e., availability of learning resources in the home and parent educational level) to students' educational engagement. Based on these findings, school social workers will need to be more attentive to utilizing macro-level interventions (i.e., community organization, interagency coordination) to achieve the organizational restructuring needed to address future challenges. The support found for the Participation-Identification model supports a shift in school social workers' attention from reactive attempts to improve the affective-interpersonal lives of students to proactive attention to their academic lives. The model concentrates school social work practices on the central mission of schools, which is educational engagement. School social workers guided by this model would be encouraged to seek changes in school policies and organization that would facilitate educational engagement. ^

Use of structural equation modeling to examine the association between breast cancer risk perception and repeat screening mammography among United States women

Breast cancer is the second leading cause of cancer death in United States women, estimated to be diagnosed in 1 out of 8 women in their lifetime. Screening mammography detects breast cancer in its pre-clinical stages when treatment strategies have the greatest chance of success, and is currently the only population-wide prevention method proven to reduce the morbidity and mortality associated with breast cancer. Research has shown that the majority of women are not screened annually, with estimates ranging front 6% - 30% of eligible women receiving all available annual mammograms over a 5-year or greater time frame. Health behavior theorists believe that perception of risk/susceptibility to a disease influences preventive health behavior, in this case, screening mammography The purpose of this dissertation is to examine the association between breast cancer risk perception and repeat screening mammography using a structural equation modeling (SEM) framework. A series of SEM multivariate regressions were conducted using self-reported, nationally representative data from the 2005 National Health Interview Survey. Interaction contrasts were tested to measure the potential moderating effects of variables which have been shown to be predictive of mammography use (physician recommendation, economic barriers, structural barriers, race/ethnicity) on the association between breast cancer risk perception and repeat mammography, while controlling for the covariates of age, income, region, nativity, and educational level. Of the variables tested for moderation, results of the SEM analyses identify physician recommendation as the only moderator of the relationship between risk perception and repeat mammography, thus the potentially most effective point of intervention to increase mammography screening, and decrease the morbidity and mortality associated with breast cancer. These findings expand the role of the physician from recommendation to one of attenuating the effect of risk perception and increasing repeat screening. The long range application of the research is the use of the SEM methodology to identify specific points of intervention most likely to increase preventive behavior in population-wide research, allowing for the most effective use of intervention funds.^