Interrupted Time Series Quasi-Experiments

Researchers seek to establish causal relationships by conducting experiments.
The standard for causal proof is what Campbell and Stanly (1963) called the "true
experiment." Often, circumstances will not permit meeting all the conditions of a true
experiment. Then, a quasi-experiment is chosen. Among the various quasiexperimental
designs is one that rivals the true experiment: the interrupted time-series
design. It has become the standard method of causal analysis in applied behavioral
research.
Just what is a "cause" is a matter of deep philosophical debate. Perhaps I can
safely ignore that debate and appeal to your intuitive understanding that renders
meaningful such statements as "The nail caused the tire to go flat" or "Owning a car
causes teenagers' grades to drop." If every relationship were causal, the world would
be a simple place; but most relationships are not. In schools where teachers make
above-average salaries, pupils score above average on achievement tests. It is not safe,
however, to say that increasing teachers' salaries will cause an increase in pupils'
achievement. Business executives who take long, expensive vacations make higher
salaries than executives who don't. But will taking the summer off and touring Europe
increase your salary? Try it and find out.