Detecting, measuring, and testing dyadic patterns in the actor-partner interdependence model.

By David A. Kenny, Thomas Ledermann. Journal of family psychology, 2010

618 citations recorded by the source corpus.

Subfields: Demography, Experimental and Cognitive Psychology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/2925096451b732cf26bb92769ff4227c7f4e6203

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Citations in the corpus

Self-esteem and the quality of romantic relationships (2016, background): “An important statistical advantage of the APIM is that it accounts for the nonindependence of responses of the two partners involved in a couple (Kenny & Ledermann, 2010).”
How to Use the Actor-Partner Interdependence Model (APIM) To Estimate Different Dyadic Patterns in MPLUS: A Step-by-Step Tutorial (2016, methodology): “The fourth pattern, which is the rarest, is the partner-only pattern (Kenny & Ledermann, 2010) or the partner-oriented pattern (Kenny et al., 2006).”
Moderation in the actor-partner interdependence model (2015, methodology): “One way patterns among the main effects have been summarized is to use a parameter that Kenny and Ledermann (2010) have proposed: k is the ratio of the partner effect to the actor effect.”
Giving dyadic data analysis away: A user‐friendly app for actor–partner interdependence models (2018, methodology): “Exploration of such patterns in the APIM was first presented by Kenny and Ledermann (2010).”
Parenting stress and marital relationship as determinants of mothers' and fathers' parenting. (2013, methodology): “To do so, we followed the procedure described by Kenny and Ledermann (2010): We calculated the ratio of the partner effect to the actor effect, also called the k parameter.”
Testing Similarity Effects with Dyadic Response Surface Analysis (2018, background): “This is important insofar as each APIM pattern suggests a very different process occurring in the dyadic relationship (Kenny & Ledermann, 2010).”
Assessing Mediation in Dyadic Data Using the Actor-Partner Interdependence Model (2011, methodology): “With distinguishable members, there are six ks (two for the a effects, two for the b effects, and two for c0 effects) and each k can either be defined in terms of the exogenous (independent) or the endogenous (dependent) variable (Kenny & Ledermann, 2010).”