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Results for “Structural equation modeling”

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PubMed1985

Structural-equation models of migration: an example from the Upper Midwest USA.

"To date, most migration models have been specified in terms of a single equation, whereby a set of regional characteristics are used to predict migration rates for various kinds of spatial units. These models are inadequate in at least two respects. First, they omit any causal links between the explanatory variables, thus ignoring indirect effects between these variables and migration. Second, they ignore the possibility of reciprocal causation, or feedback effects, between migration and the explanatory variables...." The author uses data for State Economic Areas to construct a path model and simultaneous-equation model to identify both indirect and feedback effects on migration in the Upper Midwestern United States. "On the basis of the path model, it is suggested that the direct effects of many variables on migration are at least partially offset by the indirect effects, whereas the simultaneous-equation model emphasizes the reciprocal relationship between income and migration."

Americas↗
PubMed1996

A structural equations model of stress, locus of control, social support, psychiatric symptoms, and propensity to leave a job.

The main effects of (a) job stress on psychiatric symptoms and propensity to leave a job and of (b) psychiatric symptoms on propensity to leave a job and the (c) moderating effects of locus of control and social support on the relationships of job stress to psychiatric symptoms and propensity to leave a job were examined. Data collected with questionnaires completed by 526 members of the Chamber of Commerce in a southern state were analyzed using LISREL 7 (Jöreskog & Sörbom, 1988). The results indicate that role overload and role insufficiency positively influenced psychiatric symptoms and that role insufficiency, role ambiguity, and role conflict positively influenced propensity to leave a job. Overall, the moderating effects of locus of control on the relationships of stress variables to psychiatric symptoms and propensity to leave a job were significant, but similar moderating effects for social support were not.

Adult↗
PubMed2002

Twin-singleton differences in brain structure using structural equation modelling.

Twin studies are important to investigate genetic influences on variation in human brain morphology in health and disease. However, the twin method has been criticized for its alleged non-generalizability due to differences in the intrauterine and family environment of twins, compared with singletons. To test whether twin-singleton differences complicate interpretation of genetic contributions on variation in brain volume, brains from 112 pairs of twins and 34 of their siblings with a mean (standard deviation) age of 30.7 (9.6) years were scanned using MRI. The influence of birth order, zygosity and twin-sibling differences on brain volume measures was analysed using maximum-likelihood model fitting. Variances were homogeneous across birth order, zygosity and twin-singleton status. Irrespective of zygosity, intracranial volume was smaller in second-born twins compared with first-born twins and compared with siblings. Grey matter volume was smaller in second-born twins compared with first-born twins. White matter was smaller in twins compared with siblings. Differences in grey and white matter between these groups were no longer significant after correction for intracranial volume. Total brain, and lateral and third ventricle volumes were comparable in twins and singletons. In conclusion, second-born twins have a smaller intracranial volume than their first-born co-twins and siblings. This suggests aberrant early brain development in second-born twins, which is consistent with the suboptimal pre- and perinatal environment related to birth order in twins. Since other brain volume measures were comparable between the groups, twin studies can provide reliable estimates of heritabilities in brain volume measures and these can be generalized to the singleton population.

Adult↗
PubMed2001

Psychosocial factors associated with the public's willingness to pay for genetic testing for cancer risk: a structural equations model.

An adaptation of Andersen's behavioral model of health services utilization is used to examine the psychosocial and socio-demographic factors that directly and indirectly influence the likelihood of undergoing genetic susceptibility testing for cancer, and the amount of money that individuals would be willing to pay out-of-pocket for such a test. Apart from willingness and likelihood, the model also included perceived benefits and barriers, perceived susceptibility, dispositional optimism, information seeking, family history of cancer, socioeconomic status (SES), and age, and explained 30.3% of the variation in willingness. We found as hypothesized that likelihood of undergoing such tests was central to understanding willingness to pay. Being aware of genetic susceptibility testing for cancer, and talking and seeking information about it was directly associated with an increased chance of being willing to pay more, independent of other indirect associations (effects). Interventions targeting those with a family history of cancer and those with a higher SES should generate more awareness about the potential positive and negative consequences to one's family of testing, and the interface between family history of cancer and perceived susceptibility. Interventions should also motivate people to talk and seek more information about genetic testing for cancer risk to enable them take well-informed decisions.

Adult↗
PubMed2006

Medical students' clinical reasoning skills as a function of basic science achievement and clinical competency measures: a structural equation model.

BACKGROUND: The purpose of this study was to investigate the fit of a hypothesized model of medical students' diagnostic or clinical reasoning skills based on their aptitude for medical school, basic science achievement, and clinical competency measures. METHOD: A total of 589 medical students who received their MD from 1994 to 2002 participated in this study. Confirmatory factor analysis was used to evaluate the fit of theoretical models of clinical reasoning using measures of basic science and clinical knowledge. RESULTS: The results provided support for a three-factor model of medical student performance (Bentler's Comparative Fit Index = .905, standardized root mean squared residual = .054, root mean squared error of approximation = .105). The clinical reasoning skills of medical students were influenced by an independent relationship between latent variables of basic science achievement and clinical competency. CONCLUSION: The findings support a theoretical model of diagnostic or clinical reasoning that treats the basic science and clinical knowledge of medical students as distinct domains.

Aptitude Tests↗
PubMed2004

The use of item parcels in structural equation modelling: non-normal data and small sample sizes.

Maximum likelihood estimation in confirmatory factor analysis requires large sample sizes, normally distributed item responses, and reliable indicators of each latent construct, but these ideals are rarely met. We examine alternative strategies for dealing with non-normal data, particularly when the sample size is small. In two simulation studies, we systematically varied: the degree of non-normality; the sample size from 50 to 1000; the way of indicator formation, comparing items versus parcels; the parcelling strategy, evaluating uniformly positively skews and kurtosis parcels versus those with counterbalancing skews and kurtosis; and the estimation procedure, contrasting maximum likelihood and asymptotically distribution-free methods. We evaluated the convergence behaviour of solutions, as well as the systematic bias and variability of parameter estimates, and goodness of fit.

Factor Analysis, Statistical↗
PubMed1992

Structural equation modelling of some of the determinants of suicide risk.

Much of the psychological research with suicidal patients has examined, individually or in combination, correlates and predictors of the various measures in the suicide process. The present study investigated suicidal risk as an outcome measure. Several questionnaires were administered to a sample of 94 soldiers, 61 of whom had manifested some suicidal symptoms. Using LISREL analysis, the data showed that the best model had suicide risk as directly influenced by depression and indirectly by impulsivity.

Adult↗
PubMed2006

Analysing multitrait-multimethod data with structural equation models for ordinal variables applying the WLSMV estimator: what sample size is needed for valid results?

Convergent and discriminant validity of psychological constructs can best be examined in the framework of multitrait-multimethod (MTMM) analysis. To gain information at the level of single items, MTMM models for categorical variables have to be applied. The CTC(M-1) model is presented as an example of an MTMM model for ordinal variables. Based on an empirical application of the CTC(M-1) model, a complex simulation study was conducted to examine the sample size requirements of the robust weighted least squares mean- and variance-adjusted chi(2) test of model fit (WLSMV estimator) implemented in Mplus. In particular, the simulation study analysed the chi(2) approximation, the parameter estimation bias, the standard error bias, and the reliability of the WLSMV estimator depending on the varying number of items per trait-method unit (ranging from 2 to 8) and varying sample sizes (250, 500, 750, and 1000 observations). The results showed that the WLSMV estimator provided a good -- albeit slightly liberal -- chi(2) approximation and stable and reliable parameter estimates for models of reasonable complexity (2-4 items) and small sample sizes (at least 250 observations). When more complex models with 5 or more items were analysed, larger sample sizes of at least 500 observations were needed. The most complex model with 9 trait-method units and 8 items (72 observed variables) requires sample sizes of at least 1000 observations.

Humans↗
PubMed1988

A structural equation model of physician productivity.

The understanding of physicians' practicing behaviors can enhance the development of active marketing strategies. The authors investigate the effects of physician characteristics on physician productivity in a hospital setting. Use of admission records, coupled with data from a survey of physicians' perceptions of hospital operations and their commitment to the study hospital, provides useful results for determining the most effective means for promoting physician satisfaction. Information from the survey can be used to forecast both the demand for various services and the likely physician response to the improvement of services and communications between physicians and administrative staff.

Data Collection↗
PubMed1994

Utilization patterns of cohorts of elderly clients: a structural equation model.

OBJECTIVE: To identify a model that takes into account the interrelationship of health services utilization variables, and that allows examination of the utilization patterns of health services for a cohort of elderly clients. DATA SOURCES AND STUDY SETTING: The data of each client in the study were taken from three computer databases maintained for administrative purposes by the Ministry of Health in British Columbia. Time frame for the utilization variables is one year before and one year after admission to the long-term care program in BC which occurred in 1981-1982. STUDY DESIGN: A basic model was fitted to the utilization data for the year before admission and patterns of utilization were assessed for each gender-age group for the year before admission and for the two periods, using LISREL: Fifteen utilization variables were included: number of GP and specialist visits in different settings (office, home, etc.) and number of other services such as lab tests, hospital stay, etc. DATA COLLECTION: The three files were linked to produce one record per client. PRINCIPAL FINDINGS: A model was identified that fits the data well. The total effect of GP emergency room visits on hospital stay is 0.30 compared to 0.19 direct effect. The additional impact is produced via the effect of specialist consultations on hospital stay. This and similar findings by age, gender, and period are consistent with the joint dependency of utilization variables. CONCLUSIONS: The analysis shows that males and females have different utilization patterns, while age has no effect on utilization of health services by male clients and only a small effect on utilization patterns by female clients. Admission to LTC causes more specialist contacts resulting from contact with a GP and generally a more intensive use of diagnostic and surgical procedures. However, there is significantly less acute care hospital services utilization.

Age Factors↗