Confounding in Experimental Design: Definitions With Examples

What is Confounding in Experimental Design

In a factorial experiment, a large no. of experiments becomes unsuitable to be accommodated in randomized blocks because their homogeneity is uncertain.

Therefore, we need certain techniques to preserve the feature of factorial arrangement and reduce the block size to maintain their homogeneity.

To fulfill this objective, we use confounding.

In confounding, each replication is subdivided into two or more blocks of suitable size known as incomplete blocks by giving up the information about a factorial effect usually higher-order interactions.

Some factors, which are not confounded, are estimated and tested with high precision and some factors which are confounded lose their identity as they are mixed with block differences.

Generally,2nd and higher-order interactions are of little or no importance from their physical interpretation point of view, hence they are primarily chosen for confounding. Confounding is reducing block size and is applicable only in factorial experiments.

In simple words, confounding is the technique of reducing the size of replication over a number of blocks at the cost of losing some information on some effect(which is not of much practical importance).

Confounding in 2*2*2 Factorial Design

It means that there are 3 factors each at two levels and 7 treatment factors.

Confounding in experimental design
Confounding in experimental design
Forestry Bloq
Forestry Bloq
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