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Getting the most out of your family data with fSRM

Lara Stas (UGent) , Felix Schönbrodt and Tom Loeys (UGent)
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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 (Stas, Schönbrodt & Loeys, in prep.), performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented. Aim and 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. 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.
Keywords
Social Relations Model (SRM), fSRM, dyadic, R, Lavaan

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Please use this url to cite or link to this publication:

MLA
Stas, Lara, Felix Schönbrodt, and Tom Loeys. “Getting the Most Out of Your Family Data with fSRM.” International Association for Relationship Research Conference, Abstracts. 2014. Print.
APA
Stas, L., Schönbrodt, F., & Loeys, T. (2014). Getting the most out of your family data with fSRM. International Association for Relationship Research Conference, Abstracts. Presented at the International Association for Relationship Research Conference.
Chicago author-date
Stas, Lara, Felix Schönbrodt, and Tom Loeys. 2014. “Getting the Most Out of Your Family Data with fSRM.” In International Association for Relationship Research Conference, Abstracts.
Chicago author-date (all authors)
Stas, Lara, Felix Schönbrodt, and Tom Loeys. 2014. “Getting the Most Out of Your Family Data with fSRM.” In International Association for Relationship Research Conference, Abstracts.
Vancouver
1.
Stas L, Schönbrodt F, Loeys T. Getting the most out of your family data with fSRM. International Association for Relationship Research Conference, Abstracts. 2014.
IEEE
[1]
L. Stas, F. Schönbrodt, and T. Loeys, “Getting the most out of your family data with fSRM,” in International Association for Relationship Research Conference, Abstracts, Melbourne, Australia, 2014.
@inproceedings{5922940,
  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 (Stas, Schönbrodt & Loeys, in prep.), performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented.

Aim and 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. 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    = {International Association for Relationship Research Conference, Abstracts},
  keywords     = {Social Relations Model (SRM),fSRM,dyadic,R,Lavaan},
  language     = {eng},
  location     = {Melbourne, Australia},
  title        = {Getting the most out of your family data with fSRM},
  year         = {2014},
}