Skip to main content
Log in

Thinking About Data, Research Methods, and Statistical Analyses: Commentary on Sijtsma’s (2014) “Playing with Data”

  • Published:
Psychometrika Aims and scope Submit manuscript

“Averages and relationships and trends and graphs are not always what they seem. There may be more in them than meets the eye, and there may be a good deal less.”

Darrell Huff, “How to Lie with Statistics”

Abstract

We comment on Sijtsma’s (2014) thought-provoking essay on how to minimize questionable research practices (QRPs) in psychology. We agree with Sijtsma that proactive measures to decrease the risk of QRPs will ultimately be more productive than efforts to target individual researchers and their work. In particular, we concur that encouraging researchers to make their data and research materials public is the best institutional antidote against QRPs, although we are concerned that Sijtsma’s proposal to delegate more responsibility to statistical and methodological consultants could inadvertently reinforce the dichotomy between the substantive and statistical aspects of research. We also discuss sources of false-positive findings and replication failures in psychological research, and outline potential remedies for these problems. We conclude that replicability is the best metric of the minimization of QRPs and their adverse effects on psychological research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Abelson, R. P. (1995). Statistics as principled argument. Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Asendorpf, J. B., Conner, M., De Fruyt, F., De Houwer, J., Denissen, J. J., Fiedler, K., et al. (2013). Recommendations for increasing replicability in psychology. European Journal of Personality, 27, 108–119.

    Article  Google Scholar 

  • Bertamini, M., & Munafò, M. R. (2012). Bite-size science and its undesired side effects. Perspectives on Psychological Science, 7, 67–71.

    Article  PubMed  Google Scholar 

  • Button, K. S., Ioannidis, J. P., Mokrysz, C., Nosek, B. A., Flint, J., Robinson, E. S., et al. (2013). Power failure: why small sample size undermines the reliability of neuroscience. Nature Reviews Neuroscience, 14, 365–376.

    Article  PubMed  Google Scholar 

  • Cohen, J. (1962). The statistical power of abnormal-social psycological research: A review. Journal of Abnormal and Social Psycology, 65, 145–153.

    Article  Google Scholar 

  • Cohen, J. (1969). Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Cohen, J. (1994). The earth is round \((p<. 05)\). American Psychologist, 49, 997–1003.

    Article  Google Scholar 

  • Collins, A. L., & Sullivan, P. F. (2013). Genome-wide association studies in psychiatry: What have we learned. British Journal of Psychiatry, 202, 1–4.

    Article  PubMed Central  PubMed  Google Scholar 

  • Cumming, G. (2014). The new statistics why and how. Psychological Science, 25, 7–29.

    Article  PubMed  Google Scholar 

  • Fidler, F., Thomason, N., Cumming, G., Finch, S., & Leeman, J. (2004). Editors can lead researchers to confidenceintervals, but can’t make them think: Statistical reform lessons from medicine. Psychological Science, 15, 119–126.

    Article  PubMed  Google Scholar 

  • Fisher, R. A. (1925). Statistical methods for research workers. London: Oliver & Boyd.

    Google Scholar 

  • Frank, M. C., & Saxe, R. (2012). Teaching replication. Perspectives on Psychological Science, 7, 600–604.

    Article  PubMed  Google Scholar 

  • Gigerenzer, G. (1998). We need statistical thinking, not statistical rituals. Behavioral and Brain Sciences, 21, 199–200.

    Article  Google Scholar 

  • Giner-Sorolla, R. (2012). Science or art? How aesthetic standards grease the way through the publication bottleneck but undermine science. Perspectives on Psychological Science, 7, 562–571.

    Article  PubMed  Google Scholar 

  • Gray, K., & Wegner, D. M. (2013). Six guidelines for interesting research. Perspectives on Psychological Science, 8, 549–553.

    Article  PubMed  Google Scholar 

  • Harlow, L. L., Mulaik, S. A., & Steiger, J. H. (Eds.). (1997). What if there were no significance tests? Hillsdale, NJ: Erlbaum.

  • Harzing, A. W. (2011). The publish or perish book: A guide to the software. London: Tarma Software Research.

    Google Scholar 

  • Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. New York: Academic Press.

    Google Scholar 

  • Hersh, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences, 16569–16572.

  • Huff, D. (1954). How to Lie with Statistics. New York: W.W. Norton & Company.

    Google Scholar 

  • Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis: Correcting error and bias in research findings. Newbury Park, CA: Sage.

    Google Scholar 

  • Ioannidis, J. P. A. (2005). Why most published research findings are false. PLoS Medicine, 2(8), e124. doi:10.1371/journal.pmed.0020124.

    Article  PubMed Central  PubMed  Google Scholar 

  • Ioannidis, J., Munafò, M. R., Fusar-Poli, P., Nosek, B. A., & David, S. P. (2014). Publication and other reporting biases in cognitive sciences: detection, prevalence, and prevention. Trends in Cognitive Sciences, 18, 235–241.

    Article  PubMed Central  PubMed  Google Scholar 

  • John, L. K., Loewenstein, G., & Prelec, D. (2012). Measuring the prevalence of questionable research practices with incentives for truth telling. Psychological Science, 23, 524–532.

    Article  PubMed  Google Scholar 

  • Kahneman, D. (2011). Thinking: Fast and slow. New York: Farrar, Straus and Giroux.

    Google Scholar 

  • Kuhn, T. S. (1970). The Structure of Scientific Revolutions. Chicago, IL: University of Chicago Press.

    Google Scholar 

  • Lehrer, J. (2010). The truth wears off. The New Yorker, 52–57.

  • Lykken, D. T. (1968). Statistical significance in psychological research. Psychological Bulletin, 70, 1151–1159.

    Article  Google Scholar 

  • Meehl, P. E. (1978). Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, and the slow progress of soft psychology. Journal of Consulting and Clinical Psychology, 46, 806–834.

    Article  Google Scholar 

  • Neyman, J., & Pearson, E. S. (1928). On the use and interpretation of certain test criteria for purposes of statistical inference. Biomettika, 20A, 175–240, 263–294.

  • Nickerson, R. S. (2000). Null hypothesis significance testing: A review of an old and continuing controversy. Psychological Methods, 5, 241–301.

    Article  PubMed  Google Scholar 

  • Nosek, B. A., Spies, J. R., & Motyl, M. (2012). Scientific Utopia II. Restructuring incentives and practices to promote truth over publishability. Perspectives on Psychological Science, 7, 615–631.

    Article  PubMed  Google Scholar 

  • Nosek, B. A., & Lakens, D. (2014). Registered reports. Social Psychology, 45, 137–141.

    Article  Google Scholar 

  • Oakes, M. (1986). Statistical inference: A commentary for the social and behavioral sciences. New York: Wiley.

    Google Scholar 

  • Pashler, H., & Wagenmakers, E. J. (2012). Editors’ Introduction to the Special Section on replicability in psychological science. A crisis of confidence? Perspectives on Psychological Science, 7, 528–530.

    Article  PubMed  Google Scholar 

  • Ripke, S., et al. (2013). Genome-wide association analysis identifies 13 new risk loci for schizophrenia. Nature Genetics, 45, 150–159.

    Article  Google Scholar 

  • Rosenthal, R. (2001). Meta-analytic procedures for social research (2nd ed.). Beverly Hills, CA: Sage Publications.

    Google Scholar 

  • Rosnow, R. L., & Rosenthal, R. (1989). Statistical procedures and the justification of knowledge in psychological science. American Psychologist, 44, 1276–1284.

    Article  Google Scholar 

  • Rozeboom, W. W. (1960). The fallacy of the null-hypothesis significance test. Psychological Bulletin, 57, 416–428.

    Article  PubMed  Google Scholar 

  • Schmidt, F. L. (1992). What do data really mean? Research findings, meta-analysis, and cumulative knowledge in psychology. American Psychologist, 47, 1173–1181.

    Article  Google Scholar 

  • Sedlmeier, P., & Gigerenzer, G. (1989). Do studies of statistical power have an effect on the power of studies. Psychological Bulletin, 105(2), 309–316.

    Article  Google Scholar 

  • Simons, D. J. (2014). The value of direct replication. Perspectives on Psychological Science, 9, 76–80.

    Article  PubMed  Google Scholar 

  • Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22, 1359–1366.

    Article  PubMed  Google Scholar 

  • Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2013). P-Curve: A key to the file-drawer. Journal of Experimental Psychology: General, 143, 534–537.

    Article  Google Scholar 

  • Smith, M. L., Glass, G. V., & Miller, T. I. (1980). The benefits of psychotherapy. Baltimore, MD: Johns Hopkins University Press.

    Google Scholar 

  • Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124–1131.

    Article  PubMed  Google Scholar 

  • Vrij, A., Granhag, P. A., & Porter, S. (2010). Pitfalls and opportunities in nonverbal and verbal lie detection. Psychological Science in the Public Interest, 11, 89–121.

    Article  PubMed  Google Scholar 

  • Wicherts, J.M. (2014, May 24). The power paradox and the myth of the failed study. Paper presented at the Annual Convention of the Association for Psychological Science, San Francisco, California.

  • Wicherts, J. M., Bakker, M., & Molenaar, D. (2011). Willingness to share research data is related to the strength of the evidence and the quality of reporting of statistical results. PloS One, 6, e26828.

    Article  PubMed Central  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Irwin D. Waldman or Scott O. Lilienfeld.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Waldman, I.D., Lilienfeld, S.O. Thinking About Data, Research Methods, and Statistical Analyses: Commentary on Sijtsma’s (2014) “Playing with Data”. Psychometrika 81, 16–26 (2016). https://doi.org/10.1007/s11336-015-9447-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11336-015-9447-z

Keywords

Navigation