Maximum Likelihood Estimation of Structural Equation Models for Continuous Data: Standard Errors and Goodness of Fit

Maydeu-Olivares, Alberto

doi:10.1080/10705511.2016.1269606

Cited by 243 publications

(174 citation statements)

References 25 publications

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“…41 Because we oversampled children with high SDQ scores, data were weighted according to the number of children in the stratum in the population divided by the number of participating children in that specific stratum. A robust maximum likelihood estimator was used, 42 which did not presuppose multivariate normality. To assess the prospective associations between sleep duration and symptoms of psychiatric disorders, we applied fixed and hybrid dynamic panel modeling (eFigure, eEquation, eAppendix 1, and eAppendix 2 in the Supplement).…”

Section: Discussionmentioning

confidence: 99%

Association Between Objectively Measured Sleep Duration and Symptoms of Psychiatric Disorders in Middle Childhood

et al. 2019

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IMPORTANCE The long-term association between sleep duration and mental health in children is currently unknown. OBJECTIVE To investigate the prospective associations between sleep duration and symptoms of emotional and behavioral disorders at ages 6, 8, 10, and 12 years. DESIGN, SETTING, AND PARTICIPANTS This population-based cohort study obtained data from the Trondheim Early Secure Study in Trondheim, Norway. A representative, stratified random sample of children born between January 1, 2003, and December 31, 2004, were invited to participate.

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Section: Discussionmentioning

confidence: 99%

Association Between Objectively Measured Sleep Duration and Symptoms of Psychiatric Disorders in Middle Childhood

et al. 2019

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“…The size of an SEM model has been indicated by different indices, including the number of observed variables (p), the number of parameters to be estimated (q), the degrees of freedom (df = p (p + 1)/2 2q), and the ratio of the observed variables to latent factors (p/f). Recent studies have suggested that the number of observed variables (p) is the most important determinant of model size effects (Moshagen, 2012;Shi, Lee, et al, 2015, 2017. Therefore, in the current study, we define large models as SEM models with many observed indicators.…”

Section: Authors' Notementioning

confidence: 99%

Understanding the Model Size Effect on SEM Fit Indices

Shi

Lee

Maydeu-Olivares

2018

Educational and Psychological Measurement

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285

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This study investigated the effect the number of observed variables (p) has on three structural equation modeling indices: the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). The behaviors of the population fit indices and their sample estimates were compared under various conditions created by manipulating the number of observed variables, the types of model misspecification, the sample size, and the magnitude of factor loadings. The results showed that the effect of p on the population CFI and TLI depended on the type of specification error, whereas a higher p was associated with lower values of the population RMSEA regardless of the type of model misspecification. In finite samples, all three fit indices tended to yield estimates that suggested a worse fit than their population counterparts, which was more pronounced with a smaller sample size, higher p, and lower factor loading.

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“…The estimated models tested the effects of cyberbullying roles (i.e., Cyberbully, Cyber-victim, and Cyberbully-victim), coded as dummy variables (0 = No, 1 = Yes), on depressive and anxiety symptoms, and subjective well-being through the potential mediation effect of perceived family, friends, and teachers support, controlling for age and gender. The mean-and variance-adjusted maximum likelihood test statistic (MLMV) was used as the estimator, since it is robust to non-normal data, and yields the best combination of accurate standard errors and Type I error [49]. Goodness-of-fit was assessed using the root-mean-square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR).…”

Section: Statistical Analysesmentioning

confidence: 99%

Cyberbullying and Psychological Well-being in Young Adolescence: The Potential Protective Mediation Effects of Social Support from Family, Friends, and Teachers

Hellfeldt

López‐Romero

Andershed

2019

IJERPH

162

135

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In the current study, we tested the relations between cyberbullying roles and several psychological well-being outcomes, as well as the potential mediation effect of perceived social support from family, friends, and teachers in school. This was investigated in a cross-sectional sample of 1707 young adolescents (47.5% girls, aged 10–13 years, self-reporting via a web questionnaire) attending community and private schools in a mid-sized municipality in Sweden. We concluded from our results that the Cyberbully-victim group has the highest levels of depressive symptoms, and the lowest of subjective well-being and family support. We also observed higher levels of anxiety symptoms in both the Cyber-victims and the Cyberbully-victims. Moreover, we conclude that some types of social support seem protective in the way that it mediates the relationship between cyberbullying and psychological well-being. More specifically, perceived social support from family and from teachers reduce the probability of depressive and anxiety symptoms, and higher levels of social support from the family increase the probability of higher levels of subjective well-being among youths being a victim of cyberbullying (i.e., cyber-victim) and being both a perpetrator and a victim of cyber bullying (i.e., cyberbully-victim). Potential implications for prevention strategies are discussed.

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Maximum Likelihood Estimation of Structural Equation Models for Continuous Data: Standard Errors and Goodness of Fit

Cited by 243 publications

References 25 publications

Association Between Objectively Measured Sleep Duration and Symptoms of Psychiatric Disorders in Middle Childhood

Association Between Objectively Measured Sleep Duration and Symptoms of Psychiatric Disorders in Middle Childhood

Understanding the Model Size Effect on SEM Fit Indices

Cyberbullying and Psychological Well-being in Young Adolescence: The Potential Protective Mediation Effects of Social Support from Family, Friends, and Teachers

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