Understanding parameter differences between analyses employing nested data subsets

ABSTRACT We provide an analytical argument for understanding the likely nature of parameter shifts between those coming from an analysis of a data set and from a subset of that data set, 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.

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