Skip to main content Accessibility help
×
Hostname: page-component-5c6d5d7d68-wp2c8 Total loading time: 0 Render date: 2024-08-17T14:43:57.988Z Has data issue: false hasContentIssue false

20 - Sequential aspects of experiments and experimental programmes

from Part IV - Coda

Published online by Cambridge University Press:  05 November 2012

R. Mead
Affiliation:
University of Reading
S. G. Gilmour
Affiliation:
University of Southampton
A. Mead
Affiliation:
University of Warwick
Get access

Summary

Experimentation is sequential

No experiment is an island, complete of itself, as John Donne might have said if he had been interested in formal scientific experimentation. There must, presumably, have been first experiments in all scientific fields, but in modern experimentation the design of each new experiment depends in varying degrees on the information gained from previous experiments and/or other, non-experimental, studies. This information comes in many different forms which are considered in the next section.

Sometimes experiments are designed quite deliberately in sequences to achieve a final result. This happens most obviously in selection programmes where it is known that the programme will start with a very large number of possible alternatives, which will be whittled down during a sequence of experiments to one, or a small number of, best choices. Screening programmes operate in a similar fashion.

In the development of new pharmaceutical drugs there is a very formal sequence of experiments which must be completed before the new drug can be accepted as available to medical science. This process moves from an essentially screening initial stage through to a very precisely controlled final clinical trial where the ideal drug dosage will be examined for a large number of randomly allocated subjects under controlled circumstances for a broad population.

Another area where experimentation is sequential is in the search for optimal conditions when several factors may be varied. The number of factors can become very large and the process may be partly a screening process to identify which factor levels have an effect followed by a search for the optimal conditions.

Type
Chapter
Information
Statistical Principles for the Design of Experiments
Applications to Real Experiments
, pp. 528 - 537
Publisher: Cambridge University Press
Print publication year: 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×