Autoregressive and cross-lagged panel analysis for longitudinal data.

By J. Selig, T. Little. 2012

670 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/0dd66595c0041642dff8b0bd46293aa1830126a4

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Citations in the corpus

Virtuous nexus between corporate social performance and financial performance: a study of construction enterprises in China (2016, background): “Longitudinal path analysis, also known as linear panel models, is especially capable of identifying relationships between variables over time (Selig and Little, 2012).”
Searching for an optimal balance: Dual career experiences of Swedish adolescent athletes (2015, methodology): “Please cite this article in press as: Stambulova, N. B., et al., Searching for athletes, Psychology of Sport and Exercise (2014), http://dx.”
The value of job crafting for work engagement, task performance, and career satisfaction: longitudinal and quasi-experimental evidence (2019, unknown): “LCS is superior to latent growth curve models (Meredith & Tisak, 1990) and cross-lagged regression models (Selig & Little, 2012), because it considers both dynamic differences between individuals and intra-individual changes within a two-wave time series (Ferrer & McArdle, 2003).”
The Relationship Between Media Multitasking and Attention Problems in Adolescents: Results of Two Longitudinal Studies (2017, background): “However, CLPM have been strongly criticized in the past (Hamaker, Kuiper, & Grasman, 2015; Selig & Little, 2012; Slater et al., 2003).”
Nature at home and at work: Naturally good? Links between window views, indoor plants, outdoor activities and employee well-being over one year (2017, methodology): “In the model, autoregressions reveal the stability or change of ndividuals’ relative standings on the construct from one occasion o the next (Selig & Little, 2012).”
Sample Size Recommendations for Continuous-Time Models: Compensating Shorter Time Series with Larger Numbers of Persons and Vice Versa (2020, methodology): “This is the continuoustime univariate version of the popular cross-lagged panel model (e.g., Kearney, 2017; Selig & Little, 2012) with random intercepts (Hamaker et al., 2015) and one of the building blocks for more complex models for unequally spaced ESM/ EMA/AA data analysis.”
Employee intrapreneurship and work engagement: A latent change score approach (2017, background): “…advantages over other longitudinal analysis methods, such as latent growth curve models (Meredith & Tisak, 1990) and cross-lagged regression models (Selig & Little, 2012), because it considers both dynamic differences between individuals and intra-individual changes within a two-wave time series…”
The development of emotional and behavioral self-regulation and their effects on academic achievement in childhood (2018, methodology): “Only strong measurement invariance enables us to attribute potential changes to theoretical constructs and not methodological artifacts (Little, Preacher, Selig, & Card, 2007; Selig & Little, 2012).”