use.u = true bootmer函数
我有一个关于多级模型的随机效果（BLUP）的置换置信区间的问题。
我目前正在使用bootmer，并且有一个参数use.u = true，它允许人们将蓝图视为固定的，而不是重新估计它们。由于BLUP是随机变量，因此在每个Bootstrap上重新估计它们似乎是合适的，实际上，默认选项是use.u = false。
但是，基本的假设是我的簇是从一组群集中绘制的簇的随机样本。就我而言，我正在26个国家（这是一个兴趣的集群）进行调查实验，实际上并非随机绘制。尽管我有兴趣对绘制样本的较大国家 /地区人口的推论，但我也对这些集群中的每个集群都对群集的特定效果（又称烧结）感兴趣。因此，我求助于执行引导程序，以获取这些“估计”的有效置信区间。
在这种情况下，可以设置use.u = true可以吗？
但是，我不确定答案是否已转到我的案子。有人有想法吗？
I have a question about boostrapping confidence intervals for the random effects (BLUPs) of a multilevel model.
I'm currently using bootMer and there is an argument use.u=TRUE that allows one to treat the BLUPs as fixed instead of re-estimating them. Since the BLUPs are random variables it would seem appropriate to re-estimate them at each bootstrap, and indeed the default option is use.u=FALSE.
However the underlying assumption is that my clusters are a random sample of clusters drawn from a population of clusters. In my case I am running a survey experiment in 26 countries (this is the cluster of interest) which in reality were not randomly drawn. And while I am interested in drawing inferences about the larger population of countries from which my sample is drawn, I am also interested in the cluster specific effects, AKA the BLUPs, for each one of these clusters. Because of this I'm resorting to performing bootstrap to get valid confidence intervals for these "estimates".
In this case would it be OK to set use.u=TRUE?
A related question was asked here: https://stats.stackexchange.com/questions/417518/how-to-get-confidence-intervals-for-modeled-data-of-lmer-model-in-r-with-bootmer
however I'm not sure if the answer travelled to my case. Anyone have ideas?
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