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Interrupted time series analysis involves repeated observations on a single unit both preceding and following an intervention. Recently developed statistical procedures permit inferential statements about the degree and pattern of the intervention effect. Five different software packages appropriate for interrupted time series analysis were evaluated: TSX, GENTS, BMDP, SAS, and ITSE. Simulated data was generated from 44 types of series representing eleven different ARIMA models, two types of intervention, and two different series' lengths. The five programs are compared with respect to the accuracy of estimation of the error variance, pre-intervention level, post-intervention level, and slope estimates (where appropriate). Three programs produced generally satisfactory results (TSX, GENTS, and SAS), one was generally inaccurate across a wide range of models (ITSE), and one produced some inaccuracies and occasionally failed to complete the analysis (BMDP). [ABSTRACT FROM AUTHOR]