Interrupted time-series analysis with brief single-subject data.

  title={Interrupted time-series analysis with brief single-subject data.},
  author={J Crosbie},
  journal={Journal of consulting and clinical psychology},
  volume={61 6},
  • J Crosbie
  • Published 1993 in Journal of consulting and clinical psychology
Assessing change with short time-series data is difficult because visual inference is unreliable with such data, and current statistical procedures cannot control Type I error because they underestimate positive autocorrelation. This article describes these problems and shows how they can be solved with a new interrupted time-series analysis procedure (ITSACORR) that uses a more accurate estimate of autocorrelation. Monte Carlo analyses show that, with short series, ITSACORR provides better… CONTINUE READING
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