Hi all, What is a good way to use replication methods for estimation? For a dataset with no design information, only weighting remain. I know the basic principles of replication. Are there any considerations to use replication effectively? There is a public data of 15,000 people from the Census I'm using to estimate its mean and standard error for some variables. The dataset has its survey weighting, but the survey design variables are not released to the public. The clustering and stratification stage of the survey were based on geographic information, I have no where to find them. I do have GVF to compute variance of some variable estimations. After using some replication methods, my estimations are very different from the official GVF results.