Mother and Adolescent Reports of Associations Between Child Behavior Problems and Mother-Child Relationship Qualities: Separating Shared Variance from Individual Variance |
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Authors: | William J. Burk Brett Laursen |
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Affiliation: | (1) Behavioural Science Institute, Radboud University Nijmegen, Nijmegen, The Netherlands;(2) Department of Psychology, Florida Atlantic University, Boca Raton, FL, USA;(3) Developmental Psychology, Behavioural Science Institute, Radboud University Nijmegen, PO Box 9104, 6500 HE Nijmegen, The Netherlands |
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Abstract: | This study contrasts results from different correlational methods for examining links between mother and child (N = 72 dyads) reports of early adolescent (M = 11.5 years) behavior problems and relationship negativity and support. Simple (Pearson) correlations revealed a consistent pattern of statistically significant associations, regardless of whether scores came from the same reporter or from different reporters. When correlations between behavior problems and relationship quality differed, within-reporter correlations were always greater in magnitude than between-reporter correlations. Dyadic (common fate) analyses designed for interdependent data decomposed within-reporter correlations into variance shared across reporters (dyadic correlations) and variance unique to specific reporters (individual correlations). Dyadic correlations were responsible for most associations between adolescent behavior problems and relationship negativity; after partitioning variance shared across reporters, no individual correlations emerged as statistically significant. In contrast, adolescent behavior problems were linked to relationship support via both shared variance and variance unique to maternal perceptions. Dyadic analyses provide a parsimonious alternative to multiple contrasts in instances when identical measures have been collected from multiple reporters. Findings from these analyses indicate that same-reporter variance bias should not be assumed in the absence of dyadic statistical analyses. |
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