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Accuracy of an Interval Estimation of the Proportion of Second-Level Variance in Multilevel Modeling

Sat, April 14, 10:35am to 12:05pm, Westin New York at Times Square, Floor: Fifth Floor, Melville Room

Abstract

Traditionally, researchers rely upon the intraclass correlation coefficient as a point estimate of the amount of interdependency in their data. Recent methods utilizing an interval estimation of the amount of interdependency based the proportion of second-level variance between groups have been developed that avoid relying solely upon point estimates. The likelihood of committing a Type I error when using the interval estimation of the proportion of second-level variance remains unknown. The current project addressed this deficiency in knowledge utilizing simulated data to assess the accuracy of a 95% confidence interval estimation of the proportion of second-level variance (CI-PSLV). Standard errors tended to decrease as sample size increased, and the CI-PSLV captured the second level ICC in 95% of replications.

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