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Lydia Marvin

Datos Biográficos

ID7836083
NOMBRELydia Marvin
NOMBRESLydia
APELLIDOMarvin
FIRMAMARVIN L
AFILIACIONESIllinois State University
VERIFICADONo
TOTAL DE OBRAS3
TOTAL DE CITAS0
TOTAL COMO AUTOR3
TOTAL COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2020
AÑO MÁS RECIENTE DE PUBLICACIÓN2022
ÍNDICE H0
  • Understanding the Deviance Information Criterion for SEM

    Haiyan Liu, Sarah Depaoli et al.•ARTICLE•Structural Equation Modeling: A…•2022

    The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the covariance matrix Φξ as “a” parameter, and the latter places marginal priors on factor variances and co…

  • Parameter Specification in Bayesian CFA

    Sarah Depaoli, Haiyan Liu et al.•ARTICLE•Structural Equation Modeling: A…•2021

    The impact of parameter and prior specifications on Bayesian SEM estimates is examined through two simulation studies. The model of focus was a CFA. Simulation conditions for Study 1 included varying sample size, the strength of the factor loadings (also tied to issues of reliability), factor correlation strength, and estimation conditions tied to different parameter specifications. Study 2 extended these factors and included non-zero cross-loadi…

  • Sexual objectification in #MeToo and #WhyIDidntReport tweets

    Kimberly T Schneider, Anna R George et al.•ARTICLE•Self and Identity•2020

    Sexual objectification affects women negatively in a many ways (e.g., increased focus on appearance and safety), especially if they are not provided the opportunity to cope effectively. Social media platforms provide an opportunity to share experiences and receive social support. We conducted sentiment and content analyses of #MeToo and #WhyIDidntReport (WIDR) tweets with a focus on descriptions of sexual objectification. Most #MeToo tweets were …

Sin obras prominentes en esta página.

  • Sexual objectification in #MeToo and #WhyIDidntReport tweets

    Kimberly T Schneider, Anna R George et al.•ARTICLE•Self and Identity•2020

    Sexual objectification affects women negatively in a many ways (e.g., increased focus on appearance and safety), especially if they are not provided the opportunity to cope effectively. Social media platforms provide an opportunity to share experiences and receive social support. We conducted sentiment and content analyses of #MeToo and #WhyIDidntReport (WIDR) tweets with a focus on descriptions of sexual objectification. Most #MeToo tweets were …

  • Parameter Specification in Bayesian CFA

    Sarah Depaoli, Haiyan Liu et al.•ARTICLE•Structural Equation Modeling: A…•2021

    The impact of parameter and prior specifications on Bayesian SEM estimates is examined through two simulation studies. The model of focus was a CFA. Simulation conditions for Study 1 included varying sample size, the strength of the factor loadings (also tied to issues of reliability), factor correlation strength, and estimation conditions tied to different parameter specifications. Study 2 extended these factors and included non-zero cross-loadi…

  • Understanding the Deviance Information Criterion for SEM

    Haiyan Liu, Sarah Depaoli et al.•ARTICLE•Structural Equation Modeling: A…•2022

    The deviance information criterion (DIC) is widely used to select the parsimonious, well-fitting model. We examined how priors impact model complexity (pD) and the DIC for Bayesian CFA. Study 1 compared the empirical distributions of pD and DIC under multivariate (i.e., inverse Wishart) and separation strategy (SS) priors. The former treats the covariance matrix Φξ as “a” parameter, and the latter places marginal priors on factor variances and co…

Computer Science (3 obras) · Advanced Statistical Modeling Techniques (2 obras) · Bayesian probability (2 obras) · Covariance (2 obras) · Econometrics (2 obras) · Mathematics (2 obras) · Multivariate statistics (2 obras) · Prior probability (2 obras) · Statistical Methods and Bayesian Inference (2 obras) · Statistics (2 obras)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae