Understanding parameter differences between analyses employing nested
  data subsets
  We provide an analytical argument for understanding the likely nature of
parameter shifts between those coming from an analysis of a dataset and from a
subset of that dataset, assuming differences are down to noise and any
intrinsic variance alone. This gives us a measure against which we can
interpret changes seen in parameters and make judgements about the coherency of
the data and the suitability of a model in describing those data.
