Campbell (l969) argued for the interrupted time-series experiment as a useful methodology for testing intervention effects in the social sciences. The validity of the statistical hypothesis testing of time-series, is, however, dependent upon the proper identification of the underlying stochastic nature of the data. Several types of model misidentifications are examined for some commonly encountered models in the social sciences. Analytic expressions for actual Type I error and power probabilities are derived when the mathematics is tractable; simulation techniques are adopted for the remainder of the cases. Results indicate that model misidentification leads to severe perturbations of the nominal probabilities. (Author)