@inproceedings{5919660,
  abstract     = {{Introduction
Family research aims to explore family dynamics but is often limited to the examination of unidirectional processes (e.g. parenting, child effects). As the behavior of one person has consequences that go beyond that one individual, the family functioning should be investigated in its full complexity. 
The Social Relations Model (SRM; Kenny & La Voie, 1984) is a conceptual and analytical model which can disentangle family dynamics at three different levels: the individual level (actor and partner effect), the dyadic level (relationship effects) and the family level (family effect). Nonetheless, its statistical complexity may be a hurdle for family researchers.
The user-friendly R-package  fSRM that we developed performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented.

Methods
When a round robin design is used (i.e. every family member rates every other member on the same items), the etiology of the obtained dyadic scores can be unraveled using the SRM. In particular, the estimation of the SRM parameters can be based on a confirmatory factor analysis. Therefor fSRM builds on lavaan (Rosseel, 2012), a popular R-package developed for structural equation modeling. 
With fSRM, one simple line of R-code suffices to perform the required analysis. 

Results and discussion
The fSRM-output provides easy-to-interpret summary tables of SRM variances, variance decompositions, individual and dyadic reciprocities. SRM means, which may be very informative - but infrequently reported -  are straightforwardly obtained and can easily be compared between roles. Moreover, the package is suitable for both single and multigroup studies. Additional options (e.g. intragenerational similarities) are discussed.
In sum,  fSRM enables family researchers to get easily the most out of their data.}},
  author       = {{Stas, Lara and Schönbrodt, Felix and Loeys, Tom}},
  booktitle    = {{Modern Modeling Methods conference, Abstracts}},
  keywords     = {{R,Social Relation Model,lavaan}},
  language     = {{eng}},
  location     = {{Connecticut, USA}},
  title        = {{Getting the most out of your family data with the R-package fSRM}},
  year         = {{2014}},
}