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Select variables to be added to the level-2 equations as before. Click on a variable name to display
a pop-up menu. The variables MEANSES is added grand centered and SECTOR is added
uncentered to the model:
Repeat the variable selection procedure on the equation for β1 so that the variables MEANSES and
SECTOR are also added uncentered to the equation. The 1 u term at the end of the slope equation
for β1 equation is grayed out. Enable this term as described previously and save the completed
command file by using the File, Save As option. The final model is displayed below.
The final model is now displayed, as shown below. Save this model using the File, Save As option
prior to clicking Run.
The model estimated is a log-linear model for the level-1 variances, which can be generally stated
as
HLM还提供了估计分层广义线性模型的自适应Gauss-Hermite Quadrature (AGH)和
高阶拉普拉斯Laplace近似大似然法。AGH的方法已经被是有效的,尤其当集群规模小,方差分量大的时候。高阶Laplace方法需要较大的集群大学,但允许任意数量的随机效应(当集群较大时非常重要)。
From the table, it can be seen that the slope estimates are far less reliable that the intercept
estimates. The primary reason for the lack of reliability of the slopes is that the true slope variance
across schools is much smaller than the variance of the true means. Also, the slopes are estimated
with less precision than are the means because many schools are relatively homogeneous on SES.
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