Analysis of split-plot designs for robust experimentation

4 Analysis of split-plot designs for robust experimentation 

The appropriate analysis of data obtained from an experiment should be determined by the experimental design used to obtain those data. The fundamental characteristic of split-plot designs is that there are experimental units of different sizes and consequently multiple sources of variation. The analysis needs to take account of this structure and include multiple error terms and to test the significance of effects and interactions against the appropriate error term. This has been illustrated above with the three experimental arrangements for split-plot and strip-block designs. 

If there is replication of the experiment then an independent estimate of the error terms can be calculated and valid statistical tests, such as ANOVA, can be constructed. 

EXAMPLE OF A SPLIT-PLOT DESIGN USING A FRACTIONAL 

Bayesian probability plots (Box and Meyer [49]) for the contrasts from different types of experimental units. 

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