• :

    This talk will describe spike interactions, their causes and the actions to take when they are observed.  A spike interaction may be observed during an experiment or during process monitoring when an observed value or group of observed values is far from the bulk of the observations.  These values are not outliers because the same observed values will be obtained if the set of conditions is repeated.    The spike interactions are often deleterious.  When this is the case, a major goal is to understand why they occur so their future occurrence can be avoided.  We also show where a spike interaction gives a more appropriate description of a designed experiment.

    We give examples of spike interactions that we have observed.  We describe the modelling procedure that we use for spike interactions.  Our modelling procedure uses indicator variable defined for selected high order interactions.  This modelling procedure is non-hierarchical because hierarchical modelling will produce the near equality (in absolute value) of a large number of factor effects and give a much less parsimonious model.

    Mechanisms that can produce spike interactions will be described.

  • : James M. Lucas and Carmen L. Traxler
  • : J. M. Lucas and Associates and Stat-Trax
  • : James Lucas
  • : tutorial/case_study
  • : introductory/practitioner
  • : jamesm.lucas@verizon.net
  • : 3023681214
The Spike Interaction