Abstract
This chapter undertakes a philosophical examination of four prominent quantitative research methods that are employed in the behavioural sciences. It begins by outlining a scientific realist methodology that can help illuminate the conceptual foundations of behavioural research methods. Typically, these methods contribute to either the detection of empirical phenomena or the construction of explanatory theory. The methods selected for critical examination are exploratory data analysis, Bayesian confirmation theory, meta-analysis, and causal modelling. The chapter concludes with a brief consideration of directions that might be taken in future philosophical work on quantitative methods. Two additional quantitative methods, exploratory factor analysis and tests of statistical significance, are examined in more detail in separate chapters.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Anastasi, A., & Urbina, S. (1997). Psychological testing (7th ed.). Upper Saddle River, NJ: Prentice-Hall.
Bangert-Drowns, R. L. (1986). Review of developments in meta-analytic method. Psychol. Bull., 99, 388–399.
Behrens, J. T., & Yu, C.-H. (2003). Exploratory data analysis. In J. A. Schinka & W. F. Velicer (Eds.), Handbook of psychology (Vol. 2, pp. 33–64). New York: Wiley.
Bhaskar, R. (1975). A realist philosophy of science. Brighton, England: Harvester.
Bhaskar, R. (1979). The possibility of naturalism. Brighton, England: Harvester.
Block, N. J. (1976). Fictionalism, functionalism, and factor analysis. In R. S. Cohen, C. A. Hooker, & A. C. Michalos (Eds.), Boston studies in the philosophy of science (Vol. 32, pp. 127–141). Dordrecht, The Netherlands: Reidel.
Borsboom, D. (2005). Measuring the mind: Conceptual issues in contemporary psychometrics. Cambridge, England: Cambridge University Press.
Borsboom, D. (2008). Latent variable theory. Measurement: Interdisciplinary Research and Perspectives, 6, 25–53.
Bunge, M. (2008). Bayesianism: Science or-pseudoscience? International Review of Victimology, 15, 165–178.
Chow, S. L. (1996). Statistical significance: Rationale, validity, and utility. London, England: Sage.
Cliff, N. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 115–126.
Cook, T. D., Cooper, H., Cordray, D. S., Hartmann, H., Hedges, L. V., Light, R. J., et al. (1992). Meta-analysis for explanation: A casebook. New York: Russell Sage Foundation.
Earman, J. (1992). Bayes or bust? A critical examination of Bayesian confirmation theory. Cambridge, MA: MIT Press.
Efron, B., & Tibshirani, R. (1993). An introduction to the bootstrap. New York: Chapman & Hall.
Ehrenberg, A. S. C., & Bound, J. A. (1993). Predictability and prediction. Journal of the Royal Statistical Society, Part 2, 156, 167–206.
Fidell, L. S., & Tabachnick, B. G. (2003). Preparatory data analysis. In J. A. Schibehaviornka & W. F. Velicer (Eds.), Handbook of psychology (Vol. 2, pp. 115–121). New York: Wiley.
Glass, G. V. (1972). The wisdom of scientific inquiry on education. Journal of Research in Science Teaching, 9, 3–18.
Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5, 3–8.
Glass, G. V., & Kleigl, R. M. (1983). An apology for research integration in the study of psychotherapy. Journal of Consulting and Clinical Psychology, 51, 28–41.
Glass, G. V., McGaw, B., & Smith, M. L. (1981). Meta-analysis in social research. Beverly Hills, CA: Sage.
Glymour, C. N. (1980). Theory and evidence. Princeton, NJ: Princeton University Press.
Godfrey-Smith, P. (2009). Causal pluralism. In H. Beebee, C. Hitchcock, & P. Menzies (Eds.), The Oxford handbook of causation (pp. 326–337). Oxford, England: Oxford University Press.
Good, I. J. (1983). The philosophy of exploratory data analysis. Philosophy of Science, 50, 283–295.
Gottfredson, G. D. (1984). A theory-ridden approach to program evaluation. American Psychologist, 39, 1101–1112.
Gould, S. J. (1996). The mismeasure of man (2nd ed.). New York: Norton.
Greenwood, J. D. (1992). Realism, empiricism, and social constructionism. Theory and Psychology, 2, 131–151.
Haig, B. D. (1987). Scientific problems and the conduct of research. Educational Philosophy and Theory, 19, 22–32.
Haig, B. D. (2005). An abductive theory of scientific method. Psychological Methods, 10, 371–388.
Haig, B. D. (2009). Inference to the best explanation: A neglected approach to theory appraisal in psychology. American Journal of Psychology, 122, 219–234.
Harré, R., & Madden, E. H. (1975). Causal powers. Oxford, England: Blackwell.
Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. New York: Academic Press.
Hooker, C. A. (1987). A realistic theory of science. New York: State University of New York Press.
Howson, C., & Urbach, P. (2006). Scientific reasoning: The Bayesian approach (3rd ed.). La Salle, IL: Open Court.
Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings (2nd ed.). Newbury Park, CA: Sage.
Kaplan, D. (2000). Structural equation modeling: Foundations and extensions. Thousand Oaks, CA: Sage.
Kenny, D. (1979). Correlation and causation. New York: Wiley.
Kuhn, T. S. (1996). The structure of scientific revolutions (3rd ed.). Chicago, IL: University of Chicago Press (originally published, 1962).
Laudan, L. (1981). Science and hypothesis. Dordrecht, The Netherlands: Reidel.
Lipton, P. (2004). Inference to the best explanation (2nd ed.). London, England: Routledge.
Manicas, P. T. (1989). Explanation and quantification. In B. Glassner & J. D. Moreno (Eds.), The qualitative-quantitative distinction in the social sciences (pp. 179–205). Dordrecht, The Netherlands: Kluwer.
Manicas, P. T., & Secord, P. F. (1983). Implications for psychology of the new philosophy of science. American Psychologist, 38, 399–413.
Markus, K., Hawes, S. S., & Thasites, R. (2008). Abductive inference to psychological variables: Steiger’s question and best explanations in psychopathy. Journal of Clinical Psychology, 64, 1069–1088.
Maxwell, G. (1962). The ontological status of theoretical entities. In H. Feigl & G. Maxwell (Eds.), Minnesota studies in the philosophy of science (Vol. 3, pp. 3–28). Minneapolis, MN: University of Minnesota Press.
McGrew, T. (2003). Confirmation, heuristics, and explanatory reasoning. British Journal for the Philosophy of Science, 54, 553–567.
McGuire, W. J. (1997). Creative hypothesis generating in psychology: Some useful heuristics. Annual Review of Psychology, 48, 1–30.
Michell, J. (2004). The place of qualitative research in psychology. Qualitative Research in Psychology, 1, 307–319.
Mulaik, S.A. (1985) Exploratory Statistics and Empiricism. Philosophy of Science, 52(3), 410–430.
Nickles, T. (1981). What is a problem that we might solve-it? Synthese, 47, 85–118.
Nickles, T. (1987). Twixt method and madness. In N. J. Nersessian (Ed.), The process of science (pp. 41–67). Dordrecht, The Netherlands: Martinus Nijhoff.
Pratschke, J. (2003). Realistic models? Critical realism and statistical models in the social sciences. Philosophica, 71, 13–38.
Proctor, R. W., & Capaldi, E. J. (2001). Empirical evaluation and justification of methodologies in psychological science. Psychological Bulletin, 127, 759–772.
Psillos, S. (2004). Inference to the best explanation and Bayesianism =. In F. Stadler (Ed.), Induction and deduction in the sciences (pp. 83–91). Dordrecht, The Netherlands: Kluwer.
Rozeboom, W. W. (1997). Good science is abductive, not hypothetico-deductive. In L. L. Harlow, S. A. Mulaik, & J. H. Steiger (Eds.), What if there were no significance tests? (pp. 335–391). Hillsdale, NJ: Lawrence Erlbaum.
Salmon, W. C. (1984). Scientific explanation and the causal structure of the world. Princeton, NJ: Princeton University Press.
Sayer, A. (1992). Methods in social science: A realist approach (2nd ed.). London, England: Routledge.
Schmidt, F. L. (1992). What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology. American Psychologist, 47, 1173–1181.
Schmidt, F. L. (1993). Meta-analysis and cumulative knowledge. Contemporary Psychology, 38, 1163–1165.
Simon, H. A. (1985). Spurious correlation: A causal interpretation. In H. M. Blalock (Ed.), Causal models in the social sciences (2nd ed., pp. 7–21). New York: Aldine.
Smith, M. L., Glass, G. V., & Miller, T. I. (1980). The benefits of psychotherapy. Baltimore, MD: Johns Hopkins University Press.
Sohn, D. (1996). Meta-analysis and science. Theory and Psychology, 6, 229–246.
Strauss, A. L. (1987). Qualitative analysis for social scientists. New York: Cambridge University Press.
Thagard, P. (1992). Conceptual revolutions. Princeton, NJ: Princeton University Press.
Thagard, P. (1999). How scientists explain disease. Princeton, NJ: Princeton University Press.
Trout, J. D. (1998). Measuring the intentional world: Realism, naturalism, and quantitative methods in the behavioral sciences. New York, NY: Oxford University Press.
Tukey, J. W. (1962). The future of data analysis. The Annals of Mathematical Statistics, 33, 1–67.
Tukey, J. W. (1969). Analyzing data: Sanctification or detective work? American Psychologist, 24, 83–91.
Tukey, J. W. (1977). Exploratory data analysis. Reading, MA: Addison Wesley.
Tukey, J. W. (1980). We need both exploratory and confirmatory. American Statistician, 34, 23–25.
Weisberg, J. (2009). Locating IBE in the Bayesian framework. Synthese, 167, 125–143.
Wilkinson, L., & The Task Force on Statistical Inference. (1999). Statistical methods in psychology journals: Guidelines and explanations. American Psychologist, 54, 594–604.
Woodward, J. (1989). Data and phenomena. Synthese, 79, 393–472.
Yu, C.-H. (2006). Philosophical foundations of quantitative research methodology. Lanham, MD: University Press of America.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2018 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Haig, B.D. (2018). The Philosophy of Quantitative Methods. In: Method Matters in Psychology. Studies in Applied Philosophy, Epistemology and Rational Ethics, vol 45. Springer, Cham. https://doi.org/10.1007/978-3-030-01051-5_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-01051-5_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-01050-8
Online ISBN: 978-3-030-01051-5
eBook Packages: Behavioral Science and PsychologyBehavioral Science and Psychology (R0)