Research Designs in Behavioral Cardiovascular Research

  • William J. Ray
Part of the The Springer Series in Behavioral Psychophysiology and Medicine book series (SSBP)


Science is a human activity in which we attempt to establish knowledge within particular domains of interest. There have been a number of attempts to specify how science works although no satisfactory solution has yet been achieved. Understanding science in a complete sense is a difficult if not impossible task since to specify science we would also need to specify the important parameters of those performing science which we lack at this time. However, the utility of science is assumed and stands as the major way of developing and establishing knowledge. In the development of knowledge we can begin to articulate the goals in which the scientific enterprise is directed. In science we attempt to articulate at least three different types of relationships or representations. First, there are theoretical representations. Second, there are research representations. And third, there exist Quantitative representations.


Research Design Subject Design Valid Inference Discriminant Function Analysis Statistical Concern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. Barefoot, J., Dahlstrom, G., & Williams, R. (1983). Hostility, CHD incidence, and total mortality: A 25-year follow-up study of 255 physicians. Psychosomatic Medicine, 45, 59–63.PubMedGoogle Scholar
  2. Bentler, P. (1980). Multivariate analysis with latent variables: Causal modeling. Annual Review of Psychology, 31, 419–456.CrossRefGoogle Scholar
  3. Campbell, D. (1957). Factors relevant to the validity of experiments in social settings. Psychological Bulletin, 54, 297–312.PubMedCrossRefGoogle Scholar
  4. Campbell, D., & Stanley, J. (1966). Experimental and quas iexperimental designs for research. Chicago: Rand McNally.Google Scholar
  5. Cochran, W. G. (1983). Planning and analysis of observational studies. New York: Wiley.CrossRefGoogle Scholar
  6. Cook, T., & Campbell, D. (1979). Quasi-experimentation: Designs and analysis issues for field settings. Chicago: Rand McNally.Google Scholar
  7. Corse, C., Manuck, S., Cantwell, J., Giordani, B., & Mathews, K. (1982). Coronary-prone behavior pattern and cardiovascular response in persons with and without coronary heart disease. Psychosomatic Medicine, 44, 449–459.PubMedGoogle Scholar
  8. Cronbach, L. J. (1982). Designing evaluations of educational and social programs. San Francisco: Jossey-Bass.Google Scholar
  9. Cronbach, L. J., & Meehl, P. E. (1955). Construct validity in psychological tests. Psychological Bulletin, 52, 281–302.PubMedCrossRefGoogle Scholar
  10. Dembroski, T., MacDougall, J., Williams, R., Haney, T., & Blumenthal, J. (1985). Components of type A, hostility, and anger-in: Relationship to angiographic findings. Psychosomatic Medicine, 47, 219–233.PubMedGoogle Scholar
  11. Friedman, M., Thoresen, C., Gill, J., Powell, L., Ulmer, D., Thompson, L., Price, V., Rabin, D., Breall, W., Dicon, T., Levy, R., & Bourg, E. (1984). Alteration of type A behavior and reduction in cardiac recurrences in postmyocardial infarction patients. American Heart Journal, 108, 237–248.PubMedCrossRefGoogle Scholar
  12. Krantz, D., & Manuck, S. (1984). Acute psychophysiologic reactivity and risk of cardiovascular disease: A review and methodologic critique. Psychological Bulletin, 96, 435–464.PubMedCrossRefGoogle Scholar
  13. Lakatos, I. (1978). The methodology of scientific research programmes. London: Cambridge University Press.CrossRefGoogle Scholar
  14. Maher, B. (Ed.). (1978). Special issue: Methodology in clinical research. Journal of Consulting and Clinical Psychology 46, 595–838.Google Scholar
  15. Mark, M. (1986). Validity typologies and the logic and practice of quasi-experimentation. In W. M. Trochim (Ed.), Advances in quasi-experimental design and analysis. San Francisco: Jossey-Bass.Google Scholar
  16. Nesselroade, J., & Labouvie, E. (1985). Experimental design in research on aging. In J. Birren & W. Schaie (Eds.), Handbook of the psychology of aging (2nd ed.). Princeton, NJ: Van Nostrand.Google Scholar
  17. Platt, J. R. (1964). Strong inference. Science, 146, 347–353.PubMedCrossRefGoogle Scholar
  18. Ray, W., & Ravizza, R. (1988). Methods toward a science of behavior and experience (3rd ed.). Belmont, CA: Wadsworth.Google Scholar
  19. Reichardt, C. (1986). Estimating effects. Unpublished manuscript, University of Denver.Google Scholar
  20. Scher, H., Hartman, L., Furedy, J., & Heslegrave, R. (1986). Electrocardiographic T-wave changes are more pronounced in type A than in type B men during mental work. Psychosomatic Medicine, 48, 159–166.PubMedGoogle Scholar
  21. Trochim, W. M. (Ed.). (1986). Advances in quasi-experimental design and analysis. San Francisco: Jossey-Bass.Google Scholar
  22. Voevodsky, J. (1974). Evaluation of deceleration warning light for reducing rear-end automobile collisions. Journal of Applied Psychology, 59, 270–273.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1989

Authors and Affiliations

  • William J. Ray
    • 1
  1. 1.Department of PsychologyPennsylvania State UniversityUniversity ParkUSA

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