1,137
Views
9
CrossRef citations to date
0
Altmetric
Articles

Common Mistakes in Statistical and Methodological Practices of Sport Management Research

&

References

  • Babakus, E., Ferguson, C. E., & Jöreskog, K. G. (1987). The sensitivity of confirmatory maximum likelihood factor analysis to violations of measurement scale and distributional assumptions. Journal of Marketing Research, 24, 22–28.
  • Bentler, P. M., & Yuan, K. (1999). Structural equation modeling with small samples: Test statistics. Multivariate Behavioral Research, 34, 181–197.
  • Biscaia, R., Correia, A., Rosado, A. F., Ross, S. D., & Maroco, J. (2013). Sport sponsorship: The relationship between team loyalty, sponsorship awareness, attitude toward the sponsor, and purchase intentions. Journal of Sport Management, 27, 288–302.
  • Bollen, K. A. (1989). Structural equations with latent variables. New York: John Wiley & Sons.
  • Brown, N. A., Brown, K. A., & Billings, A. C. (2015). May no act of ours bring shame: Fan-enacted crisis communication surrounding the Penn State sex abuse scandal. Communication & Sport, 3, 288–311.
  • Cooper, H., Hedges, L. V., & Valentine, J. C. (2009). The handbook of research synthesis and meta-analysis (2nd ed). New York: Russell Sage Foundation.
  • Curran, P. S., West, S. G., & Finch, J. F. (1996). The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychological Methods, 1, 16–29.
  • Dwan, K., Gamble, C., Williamson, P. R., & Kirkham, J. J. (2013). Systematic review of the empirical evidence of study publication bias and outcome reporting bias - An updated review. PloS One, 8, e66844.
  • Funk, D. C., Beaton, A., & Alexandris, K. (2012). Sport consumer motivation: Autonomy and control orientations that regulate fan behaviors. Sport Management Review, 15, 355–367.
  • George, G., Haas, M., & Pentland, A. (2014). Big data and management. Academy of Management Journal, 57, 321–326.
  • Green, S. B., Akey, T. M., Fleming, K. K., Hershberger, S. L., & Marquis, J. G. (1997). Effect of the number of scale points on chi-square fit indices in confirmatory factor analysis. Structural Equation Modeling, 4, 108–120.
  • Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis. Upper Saddle River, NJ: Pearson Prentice Hall.
  • Harman, H. H. (1976). Modern factor analysis (3rd ed.). Chicago, IL: University of Chicago Press.
  • Hill, A. B. (1965). The environment and disease: Association or causation. Proceedings of the Royal Society of Medicine, 58, 295–300.
  • Howell, D. C. (2012). Statistical methods for psychology. Belmont, CA: Wadsworth, Cengage Learning.
  • Hutchinson, S. R., & Olmos, A. (1998). Behavior of descriptive fit indexes in confirmatory factor analysis using ordered categorical data. Structural Equation Modeling, 5, 344–364.
  • James, J. D. (2018). Not all doctoral programs are create equally. Journal of Sport Management, 32, 1–10.
  • Jordan, J. S, Walker, M, Kent, A, & Inoue, Y. (2011). The frequency of nonresponse analysis in the journal of sport management. Journal Of Sport Management, 25, 229–239. doi:10.1123/jsm.25.3.229
  • Kim, K. A., & Byon, K. K. (in press). A mechanism of mutually beneficial relationship between employees and consumers: Dyadic analysis of employee-consumer interaction. Sport Management Review.
  • Kim, Y., Ko, Y. J., & James, J. D. (2011). The impact of relationship quality on attitude toward a sponsor. Journal of Business & Industrial Marketing, 26, 566–576.
  • Kim, Y., Smith, R. S., & Kwak, D. H. (2018). Feelings of gratitude: Mechanism for consumer reciprocity. European Sport Management Quarterly, 18, 307–329.
  • Kim, Y., Trail, G. T., & Ko, Y. J. (2011). The influence of relationship quality on sport consumption behaviors: An empirical examination of the relationship quality framework. Journal of Sport Management, 25, 576–592.
  • Kline, R. B. (2011). Principles and practices of structural equation modeling (3rd ed.). New York, NY: The Guilford Press.
  • Lee, J. H., Kim, H. D., Ko, Y. J., & Sagas, M. (2011). The influence of service quality on satisfaction and intention: A gender segmentation strategy. Sport Management Review, 14, 54–63.
  • Lenth, R. V. (2001). Some practical guidelines for effective sample size determination. The American Statistician, 55, 187–193.
  • Lindell, M. K., & Whitney, D. J. (2001). Accounting for common method variance in cross-sectional research designs. Journal of Applied Psychology, 86, 114–121.
  • Lipsey, M. W., & Wilson, D. B. (1993). The efficacy of psychological, educational, and behavioral treatment. Confirmation from meta-analysis. American Psychologist, 48, 1181–1209.
  • MacCallum, R. C., & Austin, J. T. (2000). Applications of structural equation modeling in psychological research. Annual Review of Psychology, 51, 201–226.
  • MacCallum, R. C., Roznowski, M., & Necowitz, L. B. (1992). Model modification in covariance structure analysis: The problem of capitalization on chance. Psychological Bulletin, 111, 490–504.
  • Machin, D., Campbell, M. J., Tan, S. B., & Tan, S. H. (2011). Sample size tables for clinical studies (3rd ed.). Hoboken, NJ: John Wiley & Sons.
  • Malhotra, N. K., Kim, S. S., & Patil, A. (2006). Common method variance in IS research: A comparison of alternative approaches and a reanalysis of past research. Management Science, 52, 1865–1883.
  • Mardia, K. V. (1985). Mardia’s test of multinormality. In S. Kotz & N. L. Johnson (Eds.), Encyclopedia of statistical sciences (Vol. 5, pp. 217–221). New York: Wiley.
  • Meredith, W. (1993). Measurement invariance, factor analysis and factor invariance. Psychometrika, 58, 525–544.
  • Morgan, S., & Winship, C. (2014). Counterfactuals and causal inference: Methods and principles for social research. New York, NY: Cambridge University Press.
  • Muthén, B. O., & Kaplan, D. (1985). A comparison of some methodologies for the factor analysis of non-normal Likert variables. British Journal of Mathematical and Statistical Psychology, 38, 171–189.
  • Nevill, A. M., Holder, R. L., & Cooper, S. M. (2007). Statistics, truth, and error reduction in sport and exercise sciences. European Journal of Sport Science, 7, 9–14.
  • Pearl, J. (2009). Causal inference in statistics: An overview. Statistics Surveys, 3, 96–146.
  • Pek, J., & MacCallum, R. C. (2011). Sensitivity analysis in structural equation models: Cases and their influence. Multivariate Behavioral Research, 46, 202–228.
  • Pieters, R. (2017). Meaningful mediation analysis: Plausible causal inference and informative communication. Journal of Consumer Research, 44, 692–716.
  • Podsakoff, P. M., MacKenzie, S. B., Lee, J., & Podsakoff, N. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88, 807–903.
  • Rogelberg, S. G., Conway, J. M., Sederburg, M. E., Spitzmüller, C., Aziz, S., & Knight, W. E. (2003). Profiling active and passive nonrespondents to an organizational survey. Journal of Applied Psychology, 88, 1104–1114.
  • Rothman, K. J., & Greenland, S. (2005). Causation and causal inference in epidemiology. American Journal of Public Health, 95, 144–150.
  • Sullivan, G. M., & Feinn, R. (2012). Using effect size - or why the p value is not enough. Journal of Graduate Medical Education, 4, 279–282.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics. Boston, MA: Allyn and Bacon.
  • Trail, G. T., & James, J. D. (2016). Seven deadly sins of manuscript writing: Reflections of two experience reviewers. Journal of Global Sport Management, 1, 142–156.
  • Trochim, W. M. K., & Donnelly, J. P. (2008). The research methods knowledge base. Mason, OH: Cengage Learning.
  • Vandenberg, R. J., & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3, 4–70.
  • VandenBos, G. R. (Ed.). (2010). Publication manual of the American Psychological Association (6th ed.). Washington, DC: American Psychological Association.
  • West, S. G., Finch, J. E., & Curran, P. J. (1995). Structural equation models with non-normal variables: Problems and remedies. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 56–75). Thousand Oaks, CA: Sage.
  • Zhang, J. J. (2015). What to study? That is a question: A conscious thoughts analysis. Journal of Sport Management, 29, 1–10.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.