Combined Effect of Many Causes

In the preceding example of an experiment on the benefit of a new plant food, it was agreed by implication that the addition of the plant food to the nourishment protocol of a subject plant did not, by its presence, in any way influence the other items of care. Suppose that a particular plant’s physiology was such that to digest the experimental food, it needed an extra supply of water. This was denied to the plant on the grounds that the quantity and schedule of watering should differ from those used for the control plants. If the need for the extra supply of water were known beforehand and were provided, the benefit of the plant food could be even greater. On the other hand, because this need was denied, there could even be a deleterious effect instead of a gain. In paired comparison experiments of medicines on humans, such “unknown” effects can be even more pronounced. If some of the subjects, for instance, develop an allergy to the new drug, while other subjects benefit remarkably, the inference from the experiment will be inconclusive. These hypothetical, but possi­ble, cases have this in common: several causes operate simulta­neously and yield a combined and summary effect. When such effect is to be observed or quantified, the relative significance of each cause needs to be analyzed in the context of its being one of many causes, not acting independently, and with the possibility of influencing and being influenced by other causes in its contri­bution toward the summary effect. Many successful attempts to face such problems in agriculture, biology, medicine, education, sports, engineering, and other sciences are collectively known as factorial design of experiments; this topic is dealt with in Chapters 8 and 9.

Source: Srinagesh K (2005), The Principles of Experimental Research, Butterworth-Heinemann; 1st edition.

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