The current study focused on dyadic discrepancy, the difference between two individuals. A Monte Carlo simulation was used to compare three dyadic discrepancy estimation methods across a variety of potential research conditions, including variations on intraclass correlation, cluster number, reliability, effect size, and effect size variance. The methods compared were: raw score difference (RSD); empirical Bayes estimate of slope in multilevel modeling (EBD); and structural equation modeling estimate (SEM). Accuracy and reliability of the discrepancy estimate and the accuracy of prediction when using the discrepancy to predict an outcome were examined. The results indicated that RSD and SEM, despite having poor reliability, performed better than EBD when predicting an outcome. The results of this research provide methodological guidance to researchers interested in dyadic discrepancies.
| Identifer | oai:union.ndltd.org:unt.edu/info:ark/67531/metadc1703431 |
| Date | 05 1900 |
| Creators | McEnturff, Amber L |
| Contributors | Henson, Robin K, Chen, Qi, Mehta, Smita, Nimon, Kim |
| Publisher | University of North Texas |
| Source Sets | University of North Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis or Dissertation |
| Format | vii, 72 pages, Text |
| Rights | Public, McEnturff, Amber L, Copyright, Copyright is held by the author, unless otherwise noted. All rights Reserved. |
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