Longitudinal Structural Equation Modeling

By T. Little. 2013

1,972 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1d5373ab3adc6348d68749478e734b98215b1850

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Citations in the corpus

A resources perspective on when and how proactive work behaviour leads to employee withdrawal (2019, background): “Using latent variables has the advantage of accounting for measurement error (Little, 2013).”
Exploring the Effect of Disability, Race-Ethnicity, and Socioeconomic Status on Scores on the Self-Determination Inventory: Student Report (2018, methodology): “The scale of the latent variable was set with effects coding to obtain final estimates that were in the metric of the original questions (Little, 2013).”
Moral Disengagement About Cyberbullying and Parental Monitoring: Effects on Traditional Bullying and Victimization via Cyberbullying Involvement (2018, background): “The initial robust model fit was satisfactory, χ2(160) = 367.69 (p < .01); root mean square error approximation (RMSEA) = .04 (90% confidence interval [CI] = [.04, .05]); non-normed fit index (NNFI) = .92; comparative fit index (CFI) = .93, scaling correction factor = 1.29 (Little, 2013).”
Is workplace bullying related to the personality traits of victims? A two-year prospective study (2015, methodology): “For the structural regression analyses of prospective data, we followed the guidelines presented by Little (2013).”
Assessing the professional identity of primary student teachers: Design and validation of the Teacher Identity Measurement Scale (2020, methodology): “This comparison is possible because the second-order model is nested in the first-order correlated model (Little, 2013).”
Teachers’ classroom management self-efficacy, perceived classroom management and teaching contexts from beginning until mid-career (2020, unknown): “Correlations were specified among all latent factors within the same measurement occasion, as well as the residual variances of same worded items across measurement occasions (Little, 2013).”
Causality Between High-Performance Work Systems and Organizational Performance (2017, background): “Autocorrelated errors were accommodated in testing the longitudinal panel model (Little, 2013), reflecting systematic measurement error over time (Gerhart et al., 2000).”
Informative tools for characterizing individual differences in learning: Latent class, latent profile, and latent transition analysis (2017, background): “In latent growth models, intercept and slope variables represent individuals' ability at a certain measurement point and its growth (i.e., learning) over time (Little, 2013).”
Mindfulness Facets and Depression in Adolescents: Rumination as a Mediator (2016, unknown): “08 (Little 2013).”
On the dark side of work: a longitudinal analysis using self-determination theory (2017, methodology): “Therefore, autoregressive paths were added between Time 1 and Time 3, Time 1 and Time 4, and Time 2 and Time 4, as recommended by Little (2013).”
Prevention of Cyberbullying and Cyber Victimization: Evaluation of the ViSC Social Competence Program (2015, background): “Little, 2013): the comparative fit index (CFI) with values greater than .90 indicating acceptable fit, and the root mean square error of approximation (RMSEA) and standardized root mean square residual (SRMR), with values smaller than .08 indicating acceptable fit.”