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  • 标题:Adequate Sample Sizes for a Three-Level Growth Model
  • 本地全文:下载
  • 作者:Lee, Eunsoo ; Hong, Sehee
  • 期刊名称:Frontiers in Psychology
  • 电子版ISSN:1664-1078
  • 出版年度:2021
  • 卷号:12
  • 页码:2617
  • DOI:10.3389/fpsyg.2021.685496
  • 出版社:Frontiers Media
  • 摘要:Multilevel models have been developed for addressing data that come from a hierarchical structure. In particular, due to the increase of longitudinal studies, a three-level growth model is frequently used to measure the change of individuals who are nested in groups. In multilevel modeling, sufficient sample sizes are needed to obtain unbiased estimates and enough power to detect individual or group effects. However, there are few sample size guidelines for three-level growth models. Therefore, it is important that researchers recognize the possibility of unreliable results when sample sizes are small. The purpose of this study is to find adequate sample sizes for a three-level growth model under realistic conditions. A Monte Carlo simulation was performed under 12 conditions: (1) level-2 sample size (10, 30), (2) level-3 sample size (30, 50, 100) (3) intraclass correlation at level-3 (0.05, 0.15). The study examined the following outcomes: convergence rate, relative parameter bias, mean square error (MSE), 95% coverage rate and power. The results indicate that estimates of the regression coefficients are unbiased, but the variance component tends to be inaccurate with small sample sizes.
  • 关键词:Three-level growth model; Sample Size; Intraclass correlation; Monte Carlo simulation study; Multilevel (hierarchical) modeling
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