Last week I asked how I might analyze a time-series type of before-
after design, one subject at a time (with due regard for the dubious
charm of such a quasi-experimental design). For example, one might
collect a week of baseline on something, then a week of data under
treatment. 

I'd like to thank everyone who contributed to that thread, even though
I eventually found the answer for myself (no, this wasn't a plant).

The answer is to use a method known, among other names, as an
interrupted time-series analysis, which calculates autocorrelations. 
In case anyone's interested, I've appended a number of references
below. But the jewel in the crown is a paper I found by Crosbie
(1993). He developed a variant of this analysis he calls ITSACORR, and
provides a standing offer of a programme to calculate it. 

48 hours later, the programme was up and running on my computer. It's
really neat.

-Stephen

References

Crosbie, J. (1993). Interrupted time-series analysis with brief
  single-subject data. Journal of Consulting and Clinical Psychology,
  61, 966-974

Jones, R. et al (1977). Time-series analysis in operant research.
  Journal of Applied Behavior Analysis, 10, 151-166.

Hartmann, D. et al (1980). Interrupted time-series analysis and
  its application to behavioral data. Journal of Applied Behavior
  Analysis, 13, 543-559.

McDowall, D. et al (1980). Interrupted time series analysis. Sage.

Hogenraad, R. et al (1997). The enemy within: autocorrelation bias
  in content analysis of narratives. Computers and the Humanities, 
  30, 433-439. [the abstract indicates that ITSACORR and other
  methods are recommended to deal with this problem]

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Stephen Black, Ph.D.                      tel: (819) 822-9600 ext 2470
Department of Psychology                  fax: (819) 822-9661
Bishop's University                    e-mail: [EMAIL PROTECTED]
Lennoxville, QC           
J1M 1Z7                      
Canada     Department web page at http://www.ubishops.ca/ccc/div/soc/psy
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