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The Time-Series Analysis of Self-reported Headache Sequences

Published online by Cambridge University Press:  06 October 2014

Robert A. M. Gregson
Robert A. M. Gregson*
Affiliation:
University of New England
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Abstract

Individual case histories collected variously in Europe and in Australia, recorded over long unbroken sequences, on a daily self-report basis, are potentially analysable as time series. The assessment of spontaneous changes in the dynamics of headache generation and attenuation, and the consequences, if any, of superimposed therapeutic intervention, require that we treat the self-report ratings of headache intensity and duration as a multistate process which is highly autoregressive. Some strong insights into individual differences both in chronic headache patterns, and in response to treatment, are obtained. Of particular interest are individual differences in cyclical and quasi-periodic headaches and in the possible causality of such differences.

Type
Research Article
Information
Behaviour Change , Volume 4 , Issue 2 , June 1987 , pp. 6 - 13
Copyright
Copyright © The Author(s) 1987

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References

REFERENCES

Allen, R. J. (1983). Human stress, its nature and control, Minneapolis: Burgess.Google Scholar
Basar, E., Flohr, H., Haken, H., & Mandell, A. J. (eds). (1983). Synergetics of the brain. Berlin: Springer-Verlag.CrossRefGoogle Scholar
Chatfield, C. (1979). Inverse autocorrelations. Journal of the Royal Statistical Society Series A, 142, 363–377.Google Scholar
Culpeper, N. (1652). The English physician; or an Astrologo—Physical discourse on the vulgar herbs of this nation. London.Google Scholar
Freeman, W. J. (1975). Mass action in the nervous system. New York: Academic Press.Google Scholar
Gregson, R. A. M. (1983). Time series in psychology. New Jersey: Erlbaum.Google Scholar
Gregson, R. A. M. (1984). Misidentification of minimum order structures in psychological time series. Paper presented at Osnabruck Mathematical Psychology Meeting, Federal Republic of Germany.Google Scholar
Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65, 297–304.CrossRefGoogle Scholar
Oxley, J., Sanz, D., & Meinardi, H. (eds). (1983). Chronic toxicity of anti-epileptic drugs. New York: Raven.Google Scholar
Schulz, W. (1982). Kombination von Gesprächstherapie mit Entspannungstechniken. Dargestellt am Beispiel von Kopfschmerzpatienten. In Howe, J. (Ed.), Methodenkombination in der Gesprächstherapie. Weinhein: Beltz.Google Scholar
Scientific Computing Associates (1985). SCA system for univariate-multivariate time series, De Kalb, Illinois: SCA, 1983.Google Scholar
Tiao, G. C., & Tsay, R. S. (1981). Identification of nonstationary and stationary ARMA models. American Statistical Association—Business and Economic Statistics Section Proceedings. 308–313.Google Scholar