scholarly journals Development of weighted model fit indexes for structural equation models using multiple imputation

2011 ◽  
Author(s):  
Cherie Joy Kientoff
Keyword(s):  
Multiple Imputation ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Model Fit ◽  
Weighted Model ◽  
Fit Indexes

Measuring the Big Five in Self-Report and Other Ratings

2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara
Keyword(s):  
Big Five ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Error Variance ◽  
The Self ◽  
Self Report ◽  
Sources Of Information ◽  
Third Person ◽  
Fit Indexes ◽  
Response Modes

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.

Forced Zero Cross-Loading Misspecifications in Measurement Component of Structural Equation Models

Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson
Keyword(s):  
Structural Equation ◽  
Structural Model ◽  
Structural Equation Models ◽  
Equation Model ◽  
Model Fit ◽  
Model Specification ◽  
Simulation Design ◽  
Measurement Models ◽  
Fit Statistics ◽  
Path Coefficients

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.

scholarly journals Cutoff criteria for overall model fit indexes in generalized structured component analysis

2020 ◽  
Vol 8 (4) ◽  
pp. 189-202
Author(s):  
Gyeongcheol Cho ◽  
Heungsun Hwang ◽  
Marko Sarstedt ◽  
Christian M. Ringle
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Goodness Of Fit ◽  
Component Analysis ◽  
Model Fit ◽  
Equation Modeling ◽  
Generalized Structured Component Analysis ◽  
Root Mean Square Residual ◽  
Fit Indexes ◽  
Cutoff Criteria

AbstractGeneralized structured component analysis (GSCA) is a technically well-established approach to component-based structural equation modeling that allows for specifying and examining the relationships between observed variables and components thereof. GSCA provides overall fit indexes for model evaluation, including the goodness-of-fit index (GFI) and the standardized root mean square residual (SRMR). While these indexes have a solid standing in factor-based structural equation modeling, nothing is known about their performance in GSCA. Addressing this limitation, we present a simulation study’s results, which confirm that both GFI and SRMR indexes distinguish effectively between correct and misspecified models. Based on our findings, we propose rules-of-thumb cutoff criteria for each index in different sample sizes, which researchers could use to assess model fit in practice.

scholarly journals A multiple imputation score test for model modification in structural equation models.

2020 ◽  
Vol 25 (4) ◽  
pp. 393-411
Author(s):  
Maxwell Mansolf ◽  
Terrence D. Jorgensen ◽  
Craig K. Enders
Keyword(s):  
Multiple Imputation ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Score Test ◽  
Model Modification

scholarly journals Structural equation modelling the relationship between anti-fungal prophylaxis and Pseudomonas bacteremia in ICU patients.

2021 ◽  
Author(s):  
James Hurley
Keyword(s):  
Latent Variables ◽  
Structural Equation ◽  
Bacterial Infections ◽  
Structural Equation Models ◽  
Model Fit ◽  
Published Data ◽  
Icu Patients ◽  
Equation Modelling ◽  
Anti Fungal ◽  
The Relationship

Abstract Purpose Animal models implicate candida colonization facilitating invasive bacterial infections. The clinical relevance of this microbial interaction remains undefined. Observations from studies of anti-septic, antibiotic, anti-fungal, and non-decontamination-based interventions to prevent ICU acquired infection collectively serve as a natural experiment. Methods Three candidate generalized structural equation models (GSEM), with Candida and Pseudomonas colonization as latent variables, were confronted with blood culture and respiratory tract isolate data derived from 460 groups from 279 studies including studies of combined antibiotic and antifungal exposures within selective digestive decontamination (SDD) interventions. Results Introducing an interaction term between Candida colonization and Pseudomonas colonization substantially improved GSEM model fit. Model derived coefficients for singular exposure to anti-septic agents (-1.23; -2.1 to -0.32), amphotericin (-1.78; -2.79 to -0.78) and topical antibiotic prophylaxis (TAP; +1.02; +0.11 to + 1.93) versus Candida colonization were similar in magnitude but contrary in direction. By contrast, the model-derived coefficients for singular exposure to TAP, as with anti-septic agents, versus Pseudomonas colonization were weaker or non-significant. Singular exposure to amphotericin would be predicted to more than halve candidemia and Pseudomonas bacteremia incidences versus literature benchmarks for absolute differences of approximately one percentage point or less. Conclusion GSEM modelling of published data supports the postulated interaction between Candida and Pseudomonas colonization towards promoting bacteremia among ICU patients. The model implicates that anti-fungal agents have greater impact in preventing bacteremia versus TAP, which has no impact.

Exploring shy minds: Relations between shyness and creativity

2018 ◽  
Author(s):  
Maria Magdalena Kwiatkowska ◽  
Radosław Rogoza ◽  
Kristie L. Poole
Keyword(s):  
Young Adults ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Model Fit ◽  
Intellectual Curiosity ◽  
Creative Imagination ◽  
Personality Dimensions ◽  
Negatively Associated

The relation between shyness and creativity has not been fully elucidated. The aim of present study was to examine if shy individuals express their creativity in different ways, as indexed by the relation between shyness and open-mindedness and its three facets: intellectual curiosity, aesthetic sensitivity, and creative imagination. We analyzed two separate structural equation models: first treating overall open-mindedness as a predictor of shyness, and the second in which we examined the three separate facets of open-mindedness (i.e., intellectual curiosity, aesthetic sensitivity, and creative imagination). Young adults (N = 727, Mage = 22.19 years) self-reported their levels of shyness and the three facets of open-mindedness. Results revealed that although shyness was unrelated to the broader construct of open-mindedness, the differentiation of the open-mindedness facets resulted in a good model fit to the data. Specifically, shyness was negatively associated with creative imagination, but positively associated with aesthetic sensitivity. Our findings illustrate the importance of examining different components of creativity, as these seem to be differentially associated with personality dimensions such as shyness. Our findings also have theoretical implications for understanding how shy individuals may express their creativity.

scholarly journals The dyspnoea–inactivity vicious circle in COPD: development and external validation of a conceptual model

2018 ◽  
Vol 52 (3) ◽  
pp. 1800079 ◽  
Author(s):  
Maria A. Ramon ◽  
Gerben Ter Riet ◽  
Anne-Elie Carsin ◽  
Elena Gimeno-Santos ◽  
Alvar Agustí ◽  
...  
Keyword(s):  
Longitudinal Data ◽  
Exercise Capacity ◽  
Structural Equation ◽  
Structural Equation Models ◽  
External Validation ◽  
Model Fit ◽  
Vicious Circle ◽  
Chronic Obstructive ◽  
New Model ◽  
Copd Exacerbations

The vicious circle of dyspnoea–inactivity has been proposed, but never validated empirically, to explain the clinical course of chronic obstructive pulmonary disease (COPD). We aimed to develop and validate externally a comprehensive vicious circle model.We utilised two methods. 1) Identification and validation of all published vicious circle models by a systematic literature search and fitting structural equation models to longitudinal data from the Spanish PAC-COPD (Phenotype and Course of COPD) cohort (n=210, mean age 68 years, mean forced expiratory volume in 1 s (FEV1) 54% predicted), testing both the hypothesised relationships between variables in the model (“paths”) and model fit. 2) Development of a new model and external validation using longitudinal data from the Swiss and Dutch ICE COLD ERIC (International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts) cohort (n=226, mean age 66 years, mean FEV157% predicted).We identified nine vicious circle models for which structural equation models confirmed most hypothesised paths but showed inappropriate fit. In the new model, airflow limitation, hyperinflation, dyspnoea, physical activity, exercise capacity and COPD exacerbations remained related to other variables and model fit was appropriate. Fitting it to ICE COLD ERIC, all paths were replicated and model fit was appropriate.Previously published vicious circle models do not fully explain the vicious circle concept. We developed and externally validated a new comprehensive model that gives a more relevant role to exercise capacity and COPD exacerbations.

scholarly journals Optimizing Detection of True Within-Person Effects for Intensive Measurement Designs: A Comparison of Multilevel SEM and Unit-Weighted Scale Scores

2020 ◽  
Author(s):  
Jonathan Rush ◽  
Philippe Rast ◽  
Scott Michael Hofer
Keyword(s):  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Structural Equation Models ◽  
Simulated Data ◽  
Variable Model ◽  
Alternative Approach ◽  
Scale Scores ◽  
Weighted Model ◽  
The Impact

Intensive repeated measurement designs are frequently used to investigate within-person variation over relatively brief intervals of time. The majority of research utilizing these designs rely on unit-weighted scale scores, which assume that the constructs are measured without error. An alternative approach makes use of multilevel structural equation models (MSEM), which permit the specification of latent variables at both within-person and between-person levels. These models disaggregate measurement error from systematic variance, which should result in less biased within-person estimates and larger effect sizes. Differences in power, precision, and bias between multilevel unit-weighted and MSEM models were compared through a series of Monte Carlo simulations. Results based on simulated data revealed that precision was consistently poorer in the MSEM models than the unit-weighted models, particularly when reliability was low. However, the degree of bias was considerably greater in the unit-weighted model than the latent variable model. Although the unit-weighted model consistently underestimated the effect of a covariate, it generally had similar power relative to the MSEM model due to the greater precision. Considerations for scale development and the impact of within-person reliability are highlighted.

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