Activity Number:
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211
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Type:
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Contributed
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Date/Time:
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Tuesday, August 13, 2002 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing*
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Abstract - #300683 |
Title:
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Composite Procedure for Testing Level Changes in the Presence of Trend in Interrupted Time-Series Analysis
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Author(s):
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Philip Ramsey*+ and Patricia Ramsey
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Affiliation(s):
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Queens College of CUNY and Fordham University
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Address:
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, Flushing, New York, 11367, USA
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Keywords:
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Mann-Wald ; Simulation ; ARIMA Models
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Abstract:
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An ongoing series of studies has been aimed at various problems arising in the detection of intervention effects in time-series data. In the most recent published work (Ramsey & Ramsey, 2001), it was found that Gottman's version of the Mann and Wald asymptotic test for intervention effects in time-series data is a useful small sample procedure. A Monte Carlo simulation was conducted to evaluate the procedure for controlling Type I errors with varying values of autoregressive coefficients. Results indicate the procedure works better than Gottman's work originally indicated. However, in some cases, error rates can be unacceptably high. Procedures for evaluating changes in level in the presence of autocorrelation and slope were suggested and evaluated.
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