Serious criticisms of psychology’s research practices and data analysis methods date back to at least the mid-1900s after the Galtonian school of thought had thoroughly triumphed over the Wundtian school. In the wake of Bem’s (2011) recent, highly publicized study on psi phenomena in a prestigious journal, psychologists are again raising serious questions about their dominant research script. These concerns are echoed in the current paper, and Observation Oriented Modeling (OOM) is presented as an alternative approach toward data conceptualization and analysis for the social and life sciences. This approach is rooted in philosophical realism and an attitude toward data analysis centered around causality and common sense. Three example studies and accompanying data analyses are presented and discussed to demonstrate a number of OOM’s advantages over current researcher practices.
References
[1]
Bem, D.J. Feeling the future: Experimental evidence for anomalous retroactive influences on cognition and affect. J. Pers. Soc. Psychol. 2011, 100, 407–425, doi:10.1037/a0021524.
[2]
Lebel, E.; Peters, K. Fearing the future of empirical psychology: Bem’s (2011) evidence of psi as a case study of deficiencies in modal research practice. Rev. Gen. Psychol. 2011, 15, 371–379, doi:10.1037/a0025172.
[3]
Roberts, B.W. Personality psychology has a serious problem (and so do many other areas of psychology). P: The Online Newsletter for Personality Science, 2011, Issue 6. Available online: http://www.personality-arp.org/newsletter06/problem.html (accessed on 26 December 2011).
[4]
Alcock, J. Back from the future: Parapsychology and the Bem affair. Skeptical Inquirer, 2011, March/April. Available online: http://www.csicop.org/specialarticles/show/back_from_the_future (accessed on 26 December 2011).
[5]
Bakan, D. On Method: Toward a Reconstruction of Psychological Investigation; Jossey-Bass: San Francisco, CA, USA, 1967.
[6]
Meehl, P.E. Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology. J. Consult. Clin. Psych. 1978, 46, 806–834, doi:10.1037/0022-006X.46.4.806.
[7]
Danziger, K. Constructing the Subject; Cambridge University Press: Cambridge, UK, 1990.
[8]
Skinner, B.F. A case history in scientific method. Am. Psychol. 1956, 11, 221–233, doi:10.1037/h0047662.
[9]
Wagenmakers, E.J.; Wetzels, R.; Borsboom, D.; van der Maas, H. Why psychologists must change the way they analyze their data: The case of psi. J. Pers. Soc. Psychol. 2011, 100, 426–432, doi:10.1037/a0022790.
[10]
Grice, J.W. Observation Oriented Modeling: Analysis of Cause in the Behavioral Sciences; Academic Press: San Diego, CA, USA,, 2011.
[11]
Pearson, K. The Grammar of Science; Meridian: New York, NY, USA, 1892. (reprinted in 1957)..
[12]
Lamiell, J.T. Statisticism in personality psychologists’ use of trait constructs: What is it? How was it contracted? Is there a cure? New Ideas Psychol. 2011. (in press).
[13]
Buss, D.; Larsen, R.; Westen, D.; Semmelroth, J. Sex differences in jealousy: Evolution, physiology, and psychology. Psychol. Sci. 1992, 3, 251–255, doi:10.1111/j.1467-9280.1992.tb00038.x.
[14]
Buss, D.M.; Larsen, R.J.; Westen, D. Sex differences in jealousy: Not gone, not forgotten, and not explained by alternative hypotheses. Psychol. Sci. 1996, 7, 373–375, doi:10.1111/j.1467-9280.1996.tb00392.x.
[15]
DeSteno, D.A.; Salovey, P. Evolutionary origins of sex differences in jealousy? Questioning the “fitness” of the model. Psychol. Sci. 1996, 7, 367–372, doi:10.1111/j.1467-9280.1996.tb00391.x.
[16]
Harris, C.R.; Christenfeld, N. Gender, jealousy, and reason. Psychol. Sci. 1996, 7, 364–366, doi:10.1111/j.1467-9280.1996.tb00390.x.
[17]
Pearl, J. Causality: Models, Reasoning, and Inference, 2nd ed.; Cambridge University Press: Cambridge, UK, 2009.
[18]
Pearl, J. The causal foundations of structural equation modeling. Handbook of Structural Equation Modeling; Guilford Press: New York, NY, USA, 2012. Available online: http://ftp.cs.ucla.edu/pub/stat_ser/r370.pdf (accessed on 26 December 2011, in press).
[19]
Collins, L.; Graham, J.; Flaherty, B. An alternative framework for defining mediation. Multivar. Behav. Res. 1998, 33, 295–312, doi:10.1207/s15327906mbr3302_5.
[20]
Von Eye, A. Configural Frequency Analysis: Methods, Models, and Applications; Psychology Press: London, UK, 2002.
[21]
Norenzayan, A.; Hansen, I. Belief in supernatural agents in the face of death. Pers. Soc. Psychol. B 2006, 32, 174–187, doi:10.1177/0146167205280251.
[22]
Wallace, W.A. The Modeling of Nature; Catholic University Press: Washington, DC, USA, 1996.
[23]
Harré, R. The positivist-empiricist approach and its alternative. In Human Inquiry; Reason, P., Rowan, J., Eds.; Wiley: New York, NY, USA, 1981; pp. 3–17.
[24]
Michell, J. Measurement in Psychology: Critical History of a Methodological Concept; Cambridge University Press: Cambridge, UK, 1999.
[25]
Michell, J. Qualitative research meets the ghost of Pythagoras. Theor. Psychol. 2011, 21, 241–259, doi:10.1177/0959354310391351.
[26]
Kelly, G.A. Behavior: The Control of Perception; Norton: New York, NY, USA, 1955.
[27]
Powers, W.T. Behavior: The Control of Perception; Benchmark Publications: New Canaan, CT, USA, 2005.
[28]
Powers, W.T. Living Control Systems III: The Fact of Control; Benchmark Publications: New Canaan, CT, USA, 2008.
[29]
Rychlak, J.F. A Philosophy of Science for Personality Theory, 2nd ed.; Krieger Publishing: Malabar, FL, USA, 1985.
[30]
Rychlak, J.F. The Psychology of Rigorous Humanism, 2nd ed.; New York University Press: New York, NY, USA, 1988.
[31]
Moving from positivsm to realism here primarily entails revitalizing three important aspects of an Aristotelian view of science. First, science must be regarded as the investigation of causes and effects rather than as mere description and prediction. Second, the four-fold (material, formal, efficient, final) view of causality must thoroughly supplant Hume's skeptical notion of causation. Finally, if causes are understood as inhering in the things of nature, then any pursuit of causes must assume that the things of nature are indeed knowable, contrary to Kant's famous dictum. An ancillary concern regards overturning the "quantitative imperative" [24,25] that assumes the psychological phenomena worth studying are structured as continuous quantities...a bias rooted in Cartesian philosophy.
[32]
Gigerenzer, G. Mindless statistics. J. Socio-Econ. 2004, 33, 587–606, doi:10.1016/j.socec.2004.09.033.
[33]
Wilkinson, L. Task force on Statistical Inference. Statistical methods in psychology journals: Guidelines and explanations. Am. Psychol. 1999, 54, 594–604, doi:10.1037/0003-066X.54.8.594.
