Adequate Sample Sizes for a Three-Level Growth Model - Lee, Eunsoo; Hong, Sehee (Frontiers in Psychology, 2021)
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.