Abstract
The purpose of this article is to illustrate, for those unfamiliar with the methods, concomitant time series analyses and their utility in psychopathology research. In a case involving somatoform disorder, we offer a detailed illustration of these analytic procedures where hypotheses regarding psychosocial antecedents of somatic symptoms are tested. Also portrayed are methods for describing across-time trends and cycles in longitudinal data. Included is a discussion of other clinical questions amenable to a time series approach, as well as a consideration of practical issues in the design of such studies.
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Aiken, L. S., West, S. G., Sechrest, L., & Reno, R. R. (1990). Graduate training in statistic methodology, and measurement in psychology: A survey of PhD programs in North America.American Psychologist, 45, 721–734.
American Psychiatric, Association (1987).Diagnostic and statistical manual of mental disorders (3rd ed., rev.). Washington, DC: Author.
Barnett, P. A., & Gotlib, I. H. (1988). Psychosocial functioning and depression: Distinguishing among antecedents, concomitants, and consequences.Psychological Bulletin, 104, 97–126.
Beck, A. T., Epstein, E., Harrison, R. P., & Emery, G. (1983).Development of the Sociotrophy-Autonomy Scale: A measure of personality factors in psychopathology. Unpublished manuscript, University of Pennsylvania, Philadelphia.
Box, G. E. P., & Jenkins, G. M. (1976).Time-series analysis: forecasting and control (rev. ed.). San Francisco: Holden-Day.
Brockwell, P. J., & Davis, R. A. (1991).Time series: Theory and methods (2nd ed.). New York: Springer-Verlag.
Bryk, A. S., & Raudenbush, S. W. (1991).Hierarchical linear models for social and behavioral research: Applications and data analysis methods. Newbury Park, CA: Sage.
Burman, B., & Margolin, G. (1992). Analysis of the association between marital relationships and health problems: An interactional perspective.Psychological Bulletin, 112, 39–63.
Catalano, R. A., Dooley, D., & Jackson, R. (1983). Selecting a time-series strategy.Psychological Bulletin, 94, 506–523.
Cohen, S., & Williamson, G. M. (1991). Stress and infectous disease in humans.Psychological Bulletin, 109, 5–24.
Collins, L. M., & Horn, J. L. (Eds.). (1991).Best methods for the analysis of change: Recent advances, unanswered questions, future directions, Washington, DC: American Psychological Association.
Cook, T., & Campbell, D. (1979).Quasi-experimentation: Design and analysis issues for field settings. Boston: Houghton Mifflin.
Cook, T. D., Dintzer, L., & Mark, M. M. (1980). The causal analysis of concomitant time series.Applied Social Psychology Annual, 1, 93–135.
Derogatis, L. R., & Spencer, P. M. (1982).The Brief Symptom Inventory: Administration, scoring, and procedures manual I. Baltimore: Clinical Psychometric Research.
Dunn, N. J., Jacob, T., Hummon, N., & Sielhamer, R. A. (1987). Marital stability in alcoholic-spouse relationships as a function of drinking pattern and location.Journal of Abnormal Psychology, 96, 99–107.
Epstein, S. (1979). The stability of behavior: I. On predicting most of the people much of the time.Journal of Personality and Social Psychology, 37, 1097–1126.
Epstein, S. (1980). The stability of behavior: II. Implications for psychological research.American Psychologist, 35, 790–806
Games, P. A. (1990). Alternative analyses of repeated-measures designs by ANOVA and MANOVA. In A. von Eye (Ed.),Statistical methods in longitudinal research (Vol. 1, pp. 81–121). New York: Academic Press.
Glass, G. V., Willson, V. L., & Gottman, J. M. (1975).Design and analysis of time-series experiments. Boulder: Colorado Associated University Press.
Gollob, H. F., & Reichardt, C. S. (1987). Taking account of time lags in causal models.Child Development, 58, 80–92.
Gollob, H. F., & Reichardt, C. S. (1991). Interpreting and estimating indirect effects assuming time lags really matter. In L. M. Collins & J. L. Horn (Eds.),Best methods for the analysis of change: Recent advances, unanswered questions, future directions (pp. 243–263). Washington, DC: American Psychological Association.
Gottman, J. M. (1981).Time series analysis: A comprehensive introduction for social scientists. New York: Cambridge University Press.
Haugh, L. D., & Box, G. E. P. (1977). Identification of dynamic regression (distributed lag) models connecting two time series.Journal of the American Statistical Association, 72, 121–130.
Hokanson, J. E., & Butler, A. C. (1992). A cluster analysis of depressed college students' social behaviors.Journal of Personality and Social Psychology, 62, 273–280.
Hokanson, J. E., Stader, S. R., Flynn, H. A., & Tate, R. L. (1992).The Daily Experiences Survey: An instrument for daily recordings of multiple variables associated with psychopathology. Unpublished manuscript, Florida State University, Tallahassee.
Johnston, J. (1984).Econometric methods. New York: McGraw-Hill.
Joreskog, K. G. (1979). Statistical models and methods for analysis of longitudinal data. In J. Magidson (Ed.),Advances in factor analysis and structural equation models (pp. 129–169). Cambridge, MA: Abt Books.
Kendall, P. C., & Watson, D. (Eds.). (1989).Anxiety and depression: Distinctive and overlapping features. New York: Academic Press.
Kenny, D. A. (1979).Correlation and causation. New York: Wiley-Interscience.
Larsen, R. J. (1987). The stability of mood variability: A spectral analysis approach to daily mood assessments:Journal of Personality and Social Psychology, 52, 1195–1204.
Larsen, R. J. (1989). A process approach to personality psychology: Utilizing time as a facet of data. In D. M. Buss & N. Cantor (Eds.)Personality psychology: Recent trends and emerging directions (pp. 177–193). New York: Springer-Verlag.
Larsen, R. J. (1990). Spectral analysis of psychological data. In A. von Eye (Ed.),Statistical methods in longitudinal research (Vol. 2, pp. 319–349). New York: Academic Press.
Larsen, R. J., & Kasimatis, M. (1990). Individual differences in entrainment of mood to the weekly calender.Journal of Personality and Social Psychology, 58, 164–171.
Larsen, R. J., & Kasimatis, M. (1991). Day-to-day physical symptoms: Individual differences in the occurrence, duration, and emotional concomitants of minor daily illnesses.Journal of Personality, 59, 387–424.
Lazarus, R. S. (1978). A strategy for research on psychological and social factors in hypertension.Journal of Human Stress, 4, 35–40.
Levor, R. M., Cohen, M. J., Naliboff, B. D., McArthur, D., & Heuser, G. (1986). Psychosocial precursors and correlates of migraine headache.Journal of Consulting and Clinical Psychology, 54, 347–353.
Ljung, G. M., & Box, G. E. P. (1978). On a measure of lack of fit in time series models.Biometrika, 65, 297–303.
McCleary, R., & Hay, R. A. (1980).Applied time-series analysis for the behavioral sciences. Beverly Hills, CA: Sage.
McMillan, M. J., & Pihl, R. O. (1987). Premenstrual depression: A distinct entity.Journal of Abnormal Psychology, 96, 149–154.
Monroe, S. M., & Simons, A. D. (1991). Diathesis-stress theories in the context of life stress research: Implications for the depressive disorders.Psychological Bulletin, 110, 406–425.
Muthen, B. O. (1991). Analysis of longitudinal data using latent variable models with varying parameters. In L. M. Collins & J. L. Horn (Eds.),Best methods for the analysis of change: Recent advances, unanswered questions, future directions (pp. 1–17). Washington, DC: American Psychological Association.
O'Leary, A. (1990). Stress, emotion, and human immune function.Psychological Bulletin, 108, 363–382.
Pankratz, A. (1991).Forecasting with dynamic regression models. New York: John Wiley & Sons.
Priestley, M. B. (1981).Spectral analysis and time series. New York: Academic Press.
Stone, A. A., Kessler, R. C., & Haythornthwaite, J. A. (1991). Measuring daily events and experiences: Decisions for the researcher.Journal of Personality, 59, 575–608.
Tate, R. L., & Hokanson, J. E. (1993). Analyzing individual status and change with hierarchical linear models: Illustration with depression in college students.Journal of Personality, 61, 181–206.
Tennen, H., Sulls, J., & Affleck, G. (Eds.). ({dy1991}). Personality and daily experience. {jtJournal of Personality}, {vn59} ({snWhole No. 3}).
Tzelgov, J., & Henik, A. (1991). Suppression situations in psychological research: Definitions, implications, and applications.Psychological Bulletin, 109, 524–536.
von Eye, A. (Ed.). (1990a).Statistical methods in longitudinal research: Vol. I. Principles and structuring change. New York: Academic Press.
von Eye, A. (Ed.). (1990b).Statistical methods in longitudinal research: Vol. II. Time series and categorical longitudinal data. New York: Academic Press.
Weisberg, S. (1980).Applied linear regression. New York: John Wiley & Sons.
Weisse, C. S. (1992). Depression and immunocompetence: A review of the literature.Psychological Bulletin, 111, 475–489.
West, S. G., & Hepworth, J. T. (1991). Statistical issues in the study of temporal data: Daily experiences:Journal of Personality, 59, 609–662.
Wheeler, L., & Reis, H. T. (1991). Self-recording of everyday life events: Origins, types, and uses.Journal of Personality, 59, 339–354.
Wilkinson, L. (1991).SYSTAT 5.0: System for statistics [Computer program]. Evanston, IL: Systat, Inc.
Youngren, M. A., Zeiss, A., & Lewinsohn, P. M. (1975).The Interpersonal Events Schedule. Unpublished manuscript, University of Oregon, Eugene.
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The authors gratefully acknowledge the helpful comments of Richard Wagner, Edwin Megargee, Stephen West, Associate Editor Diane Arnkoff, and an anonymous reviewer.
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Hokanson, J.E., Tate, R.L., Niu, X. et al. Illustration of concomitant times series analyses in a case of somatoform disorder. Cogn Ther Res 18, 413–437 (1994). https://doi.org/10.1007/BF02357752
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DOI: https://doi.org/10.1007/BF02357752