Time series design

This design uses a series of pre- and post-measurements to determine the impact of the experiment. It attempts to measure the impact over a longer period of time than other basic methods.

The time series design appears as follows:

It assumes that the researcher will have continual access to the same test units. Consumer panels are prime examples of the application of this type of experimental design. Figure 9.4 shows some possible outcomes from experiments using a time series design.

Time series treatments

Time series treatments

FIGURE 9.4

Time series analysis

Outcome 1 : a short-lived positive effect.

Outcome 2: a long-term positive effect - market share increased. Outcome 3: a positive effect - it halted a decline in sales.

Outcome 4: seems to have no effect - fluctuation continues in the same manner. Outcome 5: seems to have no effect - growth continues in the same pattern.

Because measurements are made over a longer period of time, such extraneous factors as testing, maturation and regression tend to be neutralised. However, there is always the danger that some other event may have occurred at the same time the experiment took place and this external event could be the real cause of any changes in the observation. The problem of mortality - drop out - also increases as the length of the time series increases.

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