Editing Design of experiments (section)

==Discussion topics when setting up an experimental design==
An experimental design or randomized clinical trial requires careful consideration of several factors before actually doing the experiment.<ref>Ader, Mellenberg & Hand (2008) "Advising on Research Methods: A consultant's companion"</ref> An experimental design is the laying out of a detailed experimental plan in advance of doing the experiment. Some of the following topics have already been discussed in the principles of experimental design section:

# How many factors does the design have, and are the levels of these factors fixed or random?
# Are control conditions needed, and what should they be?
# Manipulation checks: did the manipulation really work?
# What are the background variables?
# What is the sample size? How many units must be collected for the experiment to be generalisable and have enough [[Statistical power|power]]?
# What is the relevance of interactions between factors?
# What is the influence of delayed effects of substantive factors on outcomes?
# How do response shifts affect self-report measures?
# How feasible is repeated administration of the same measurement instruments to the same units at different occasions, with a post-test and follow-up tests?
# What about using a proxy pretest?
# Are there [[Confounding|confounding variables]]?
# Should the client/patient, researcher or even the analyst of the data be blind to conditions?
# What is the feasibility of subsequent application of different conditions to the same units?
# How many of each control and noise factors should be taken into account?

The independent variable of a study often has many levels or different groups. In a true experiment, researchers can have an experimental group, which is where their intervention testing the hypothesis is implemented, and a control group, which has all the same element as the experimental group, without the interventional element. Thus, when everything else except for one intervention is held constant, researchers can certify with some certainty that this one element is what caused the observed change. In some instances, having a control group is not ethical. This is sometimes solved using two different experimental groups. In some cases, independent variables cannot be manipulated, for example when testing the difference between two groups who have a different disease, or testing the difference between genders (obviously variables that would be hard or unethical to assign participants to). In these cases, a quasi-experimental design may be used.