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Hello, I have some measurements that I am trying to fit a model to. I also have uncertainties for these measurements. Some of the measurements are not well detected, so I'd like to use a limit instead of the...

Hi, I have some measurements and their uncertainties. I'm using an uncensored subset of the data for a weighted fit (for now---I'll do a fit to the full, censored, dataset when I understand the results). survreg() reports...

Hrm, thanks. The uncertainties are what they are, though (and the model is what it is, too) -- is there an alternative to modifying them? Maybe another type of analysis that handles upper limits? Kyle On Thu, Jun 13, 2013 at...

> Survreg treats weights as case weights, and lm treats them as sampling weights. > Here is a simple example. Data set test2 has two copies of every obs in data set test. > > > test <- data.frame(x=1:6, y=c(1...

I understand that the robust variances may lead to a different standard error. I want the standard error valid for heteroscedastic data, ultimately, because I have very good estimates of the measurement variances (why I'm doing weighted fits in...

Hi Terry, Thanks for your quick reply. I am talking about uncertainty in the response. I have 2 follow up questions: 1) my understanding from the documentation is that 'id' in cluster(id) should be the same when the predictors...