Analysis Of Quasi-Experimental Time-Series Designs
Abstract:
Multivariate procedures, based on the general linear hypothesis, are outlined for inferring treatment effects in quasi-experimental time-series designs. These procedures, which take into account the dependent nature of the data obtained in time-series experiments and which require comparing the fitted regression curves for the pre-treatment and post-treatment observations, provide exact tests of significance for the various hypotheses of interest.
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