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Factor score regression with social relations model components : a case study exploring antecedents and consequences of perceived support in families

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Abstract
The family social relations model (SRM) is applied to identify the sources of variance in interpersonal dispositions in families, but the antecedents or consequences of those sources are rarely investigated. Simultaneous modeling of the SRM with antecedents or consequences using structural equation modeling (SEM) allows to do so, but may become computationally prohibitive in small samples. We therefore consider two factor score regression (FSR) methods: regression and Bartlett FSR. Based on full information maximum likelihood (FIML), we derive closed-form expressions for the regression and Bartlett factor scores in the presence of missingness. A simulation study in both a complete- and incomplete-case setting compares the performance of these FSR methods with SEM and an ANOVA-based approach. In both settings, the regression FIML factor scores as explanatory variable produces unbiased estimators with precision comparable to the SEM-estimators. When SRM-effects are used as dependent variables, none of the FSR methods are a suitable alternative for SEM. The latter result deviates from previous studies on FSR in more simple settings. As an example, we explore whether gender and past victimhood of relational and physical aggression are antecedents for family dynamics of perceived support, and whether those dynamics predict physical and relational aggression.
Keywords
MAXIMUM-LIKELIHOOD-ESTIMATION, STRUCTURAL EQUATION, R PACKAGE, ADOLESCENT ADJUSTMENT, LATENT-VARIABLES, PERCEPTIONS, BEHAVIOR, VICTIMS, PARENTS, BULLIES, factor score regression, family social relations model, perceived, support, structural equation modeling, missing data

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MLA
Loncke, Justine et al. “Factor Score Regression with Social Relations Model Components : a Case Study Exploring Antecedents and Consequences of Perceived Support in Families.” FRONTIERS IN PSYCHOLOGY 9 (2018): n. pag. Print.
APA
Loncke, J., Eichelsheim, V. I., Branje, S. J. T., Buysse, A., Meeus, W. H. J., & Loeys, T. (2018). Factor score regression with social relations model components : a case study exploring antecedents and consequences of perceived support in families. FRONTIERS IN PSYCHOLOGY, 9.
Chicago author-date
Loncke, Justine, Veroni I. Eichelsheim, Susan J. T. Branje, Ann Buysse, Wim H. J. Meeus, and Tom Loeys. 2018. “Factor Score Regression with Social Relations Model Components : a Case Study Exploring Antecedents and Consequences of Perceived Support in Families.” Frontiers in Psychology 9.
Chicago author-date (all authors)
Loncke, Justine, Veroni I. Eichelsheim, Susan J. T. Branje, Ann Buysse, Wim H. J. Meeus, and Tom Loeys. 2018. “Factor Score Regression with Social Relations Model Components : a Case Study Exploring Antecedents and Consequences of Perceived Support in Families.” Frontiers in Psychology 9.
Vancouver
1.
Loncke J, Eichelsheim VI, Branje SJT, Buysse A, Meeus WHJ, Loeys T. Factor score regression with social relations model components : a case study exploring antecedents and consequences of perceived support in families. FRONTIERS IN PSYCHOLOGY. Lausanne: Frontiers Media Sa; 2018;9.
IEEE
[1]
J. Loncke, V. I. Eichelsheim, S. J. T. Branje, A. Buysse, W. H. J. Meeus, and T. Loeys, “Factor score regression with social relations model components : a case study exploring antecedents and consequences of perceived support in families,” FRONTIERS IN PSYCHOLOGY, vol. 9, 2018.
@article{8599909,
  abstract     = {The family social relations model (SRM) is applied to identify the sources of variance in interpersonal dispositions in families, but the antecedents or consequences of those sources are rarely investigated. Simultaneous modeling of the SRM with antecedents or consequences using structural equation modeling (SEM) allows to do so, but may become computationally prohibitive in small samples. We therefore consider two factor score regression (FSR) methods: regression and Bartlett FSR. Based on full information maximum likelihood (FIML), we derive closed-form expressions for the regression and Bartlett factor scores in the presence of missingness. A simulation study in both a complete- and incomplete-case setting compares the performance of these FSR methods with SEM and an ANOVA-based approach. In both settings, the regression FIML factor scores as explanatory variable produces unbiased estimators with precision comparable to the SEM-estimators. When SRM-effects are used as dependent variables, none of the FSR methods are a suitable alternative for SEM. The latter result deviates from previous studies on FSR in more simple settings. As an example, we explore whether gender and past victimhood of relational and physical aggression are antecedents for family dynamics of perceived support, and whether those dynamics predict physical and relational aggression.},
  articleno    = {1699},
  author       = {Loncke, Justine and Eichelsheim, Veroni I. and Branje, Susan J. T. and Buysse, Ann and Meeus, Wim H. J. and Loeys, Tom},
  issn         = {1664-1078},
  journal      = {FRONTIERS IN PSYCHOLOGY},
  keywords     = {MAXIMUM-LIKELIHOOD-ESTIMATION,STRUCTURAL EQUATION,R PACKAGE,ADOLESCENT ADJUSTMENT,LATENT-VARIABLES,PERCEPTIONS,BEHAVIOR,VICTIMS,PARENTS,BULLIES,factor score regression,family social relations model,perceived,support,structural equation modeling,missing data},
  language     = {eng},
  pages        = {19},
  publisher    = {Frontiers Media Sa},
  title        = {Factor score regression with social relations model components : a case study exploring antecedents and consequences of perceived support in families},
  url          = {http://dx.doi.org/10.3389/fpsyg.2018.01699},
  volume       = {9},
  year         = {2018},
}

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