INTRODUCTION: There are so many types of experimental design that not all of them can be considered within the scope of today’s discussion. This section, therefore, is confined to describing those most commonly used in the social sciences, the humanities, public health, marketing, education, epidemiology, social work, and so on. These designs have been categorised as: the after-only experimental design; the before-and-after experimental design; the control group design; the double-control design; the comparative design; the ‘matched control’ experimental design; the placebo design.
THE AFTER-ONLY EXPERIMENTAL DESIGN: In an after-only design the researcher knows that a population is being, or has been, exposed to an intervention and wishes to study its impact on the population. In this design, information on baseline that is to say pre-test or before observation, is usually constructed on the basis of respondents’ recall of the situation before the intervention, or from information available in existing records for example secondary sources.
The change in the dependent variable is therefore measured by the difference between the before which act as the baseline, and ‘after’ data sets. Technically, this is a very faulty design for measuring the impact of an intervention as there are no proper baseline data to compare the ‘after’ observation with. Therefore, one of the major problems of this design is that the two sets of data are not strictly comparable. For example, some of the changes in the dependent variable may be attributable to the difference in the way the two sets of data were compiled. Another problem with this design is that it measures total change, including change attributable to extraneous variables; hence, it cannot identify the net effect of an intervention.
In practice, the adequacy of this design depends on having reasonably accurate data available about the prevalence of a phenomenon before the intervention is introduced. This might be the case for situations such as the impact of random breath testing on road accidents, the impact of a health programme on the mortality of a population, the impact of an advertisement on the sale of a product, the impact of a decline in mortality on the fertility of a population, or the impact of a change in immigration policy on the extent of immigration. In these situations it is expected that accurate records are kept about the phenomenon under study and so it may be easier to determine whether any change in trends is primarily because of the introduction of the intervention or change in the policy.
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