# Convergence with models with overspecified models, low noise

Hello,

This is a continuation of a different question. I am trying do some simulations to study dose/response curves with variation on blocks. My model is as follows:

stan_glmer(formula(y~logDose*sampleName+(1|block)+(0+logDose|block)),
Yes, if there is no information in the data about the cross-block variance, then it is going to be dominated by the prior, which is by default exponential, and it is quite possible that there is posterior mass too close to zero. In addition to specifying QR = TRUE, you could mess around with the prior_covariance argument.