Experiments in blocks for a non-normal response
Seminar Room 1, Newton Institute
AbstractMany industrial experiments measure a response that cannot be adequately described by a linear model with normally distributed errors. An example is an experiment in aeronautics to investigate the cracking of bearing coatings where a binary response was observed, success (no cracking) or failure (cracked). A further complication which often occurs in practice is the need to run the experiment in blocks, for example, to account for different operators or batches of experimental units. To produce more efficient experiments, block effects are often included in the model for the response. When the block effects can be considered as nuisance variables, a marginal (or population averaged) model may be appropriate, where the effect of individual blocks are not explicitly modelled. We discuss block designs for experiments where the response is described by a marginal model fitted using Generalised Estimating Equations (GEEs). GEEs are an extension of Generalised Linear Models (GLMs) that incorporate a correlation structure between experiment units in the same block; the marginal response for each observation follows an appropriate GLM. This talk will describe some design strategies for such models in an industrial context.
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