The cross-sectional research design, especially when used with self-report surveys, is held in low esteem despite its widespread use. It is generally accepted that the longitudinal design offers considerable advantages and should be preferred due to its ability to shed light on causal connections. In this paper, I will argue that the ability of the longitudinal design to reflect causality has been overstated and that it offers limited advantages over the cross-sectional design in most cases in which it is used. The nature of causal inference from a philosophy of science perspective is used to illustrate how cross-sectional designs can provide evidence for relationships among variables and can be used to rule out many potential alternative explanations for those relationships. Strategies for optimizing the use of cross-sectional designs are noted, including the inclusion of control variables to rule out spurious relationships, the addition of alternative sources of data, and the incorporation of experimental methods. Best practice advice is offered for the use of both cross-sectional and longitudinal designs, as well as for authors writing and for reviewers evaluating papers that report results of cross-sectional studies.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Antonakis, J., Bendahan, S., Jacquart, P., & Lalive, R. (2010). On making causal claims: A review and recommendations. The Leadership Quarterly, 21(6), 1086–1120. https://doi.org/10.1016/j.leaqua.2010.10.010.
Berofsky, B. (1966). Causality and general laws. The Journal of Philosophy, 63(6), 148–157. https://doi.org/10.2307/2024170.
Bolino, M. C. (1999). Citizenship and impression management: Good soldiers or good actors? The Academy of Management Review, 24(1), 82–98. https://doi.org/10.2307/259038.
Brief, A. P., Burke, M. J., George, J. M., Robinson, B. S., & Webster, J. (1988). Should negative affectivity remain an unmeasured variable in the study of job stress? Journal of Applied Psychology, 73(2), 193–198.
Chen, P. Y., & Spector, P. E. (1991). Negative affectivity as the underlying cause of correlations between stressors and strains. Journal of Applied Psychology, 76(3), 398–407. https://doi.org/10.1037/0021-9010.76.3.398.
Cole, D. A., Martin, N. C., & Steiger, J. H. (2005). Empirical and conceptual problems with longitudinal trait-state models: Introducing a trait-state-occasion model. Psychological Methods, 10(1), 3–20. https://doi.org/10.1037/1082-989X.10.1.3.
Dalal, R. S. (2005). A meta-analysis of the relationship between organizational citizenship behavior and counterproductive work behavior. Journal of Applied Psychology, 90(6), 1241–1255. https://doi.org/10.1037/0021-9010.90.6.1241.
Frese, M., & Zapf, D. (1988). Methodological issues in the study of work stress: Objective vs subjective measurement of work stress and the question of longitudinal studies. In C. L. Cooper & R. Payne (Eds.), Causes, coping and consequences of stress at work (pp. 375–411). Oxford, England: John Wiley & Sons.
Glick, W. H., Huber, G. P., Miller, C. C., Doty, D. H., & Sutcliffe, K. M. (1990). Studying changes in organizational design and effectiveness: Retrospective event histories and periodic assessments. Organization Science, 1(3), 293–312. https://doi.org/10.2307/2635007.
Glick, W. H., Jenkins, G., & Gupta, N. (1986). Method versus substance: How strong are underlying relationships between job characteristics and attitudinal outcomes? Academy of Management Journal, 29(3), 441–464.
Griffin, R. W. (1991). Effects of work redesign on employee perceptions, attitudes, and behaviors: A long-term investigation. Academy of Management Journal, 34(2), 425–435. https://doi.org/10.2307/256449.
Hausman, D. M., & Woodward, J. (1999). Independence, invariance and the causal Markov condition. The British Journal for the Philosophy of Science, 50(4), 521–583. https://doi.org/10.1093/bjps/50.4.521.
Illari, P., & Russo, F. (2014). Causality: Philosophical theory meets scientific practice. Oxford, UK: Oxford University Press.
Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15(4), 309–334. https://doi.org/10.1037/a0020761.
Kraemer, H. C., Stice, E., Kazdin, A., Offord, D., & Kupfer, D. (2001). How do risk factors work together? Mediators, moderators, and independent, overlapping, and proxy risk factors. The American Journal of Psychiatry, 158(6), 848–856. https://doi.org/10.1176/appi.ajp.158.6.848.
Meehl, P. E. (1971). High school yearbooks: A reply to Schwarz. Journal of Abnormal Psychology, 77(2), 143–148.
Mitchell, T. R., & James, L. R. (2001). Building better theory: Time and the specification of when things happen. The Academy of Management Review, 26(4), 530–547. https://doi.org/10.2307/3560240.
Nixon, A. E., Mazzola, J. J., Bauer, J., Krueger, J. R., & Spector, P. E. (2011). Can work make you sick? A meta-analysis of the relationships between job stressors and physical symptoms. Work & Stress, 25(1), 1–22. https://doi.org/10.1080/02678373.2011.569175.
Pearl, J. (2014). Interpretation and identification of causal mediation. Psychological Methods, 19(4), 459–481. https://doi.org/10.1037/a0036434.
Pindek, S., & Spector, P. E. (2016). Organizational constraints: A meta-analysis of a major stressor. Work & Stress, 30(1), 7–25. https://doi.org/10.1080/02678373.2015.1137376.
Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–569. https://doi.org/10.1146/annurev-psych-120710-100452.
Schwarzmüller, T., Brosi, P., & Welpe, I. M. (2018). Sparking anger and anxiety: Why intense leader anger displays trigger both more deviance and higher work effort in followers. Journal of Business and Psychology, 33(6), 761–777. https://doi.org/10.1007/s10869-017-9523-8.
Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.
Spector, P. E. (1992). A consideration of the validity and meaning of self-report measures of job conditions. In C. L. Cooper & I. T. Robertson (Eds.), International Review of Industrial and Organizational Psychology (pp. 123–151). West Sussex, UK: John Wiley.
Spector, P. E. (2006). Method variance in organizational research: Truth or urban legend? Organizational Research Methods, 9(2), 221–232. https://doi.org/10.1177/1094428105284955.
Spector, P. E., Bauer, J. A., & Fox, S. (2010). Measurement artifacts in the assessment of counterproductive work behavior and organizational citizenship behavior: Do we know what we think we know? Journal of Applied Psychology, 95(4), 781–790. https://doi.org/10.1037/a0019477.
Spector, P. E., & Brannick, M. T. (2011). Methodological urban legends: The misuse of statistical control variables. Organizational Research Methods, 14(2), 287–305. https://doi.org/10.1177/1094428110369842.
Spector, P. E., Fox, S., & Van Katwyk, P. T. (1999). The role of negative affectivity in employee reactions to job characteristics: Bias effect or substantive effect? Journal of Occupational and Organizational Psychology, 72(2), 205–218. https://doi.org/10.1348/096317999166608.
Spector, P. E., & Meier, L. L. (2014). Methodologies for the study of organizational behavior processes: How to find your keys in the dark. Journal of Organizational Behavior, 35(8), 1109–1119. https://doi.org/10.1002/job.1966.
Spector, P. E., & Pindek, S. (2016). The future of research methods in work and occupational health psychology. Applied Psychology: An International Review, 65(2), 412–431. https://doi.org/10.1111/apps.12056.
Spector, P. E., Rosen, C. C., Richardson, H. A., Williams, L. J., & Johnson, R. E. (2017). A new perspective on method variance: A measure-centric approach. Journal of Management, 0(0), 0149206316687295. https://doi.org/10.1177/0149206316687295.
Spector, P. E., Yang, L.-Q., & Zhou, Z. E. (2015). A longitudinal investigation of the role of violence prevention climate in exposure to workplace physical violence and verbal abuse. Work & Stress, 29(4), 325–340. https://doi.org/10.1080/02678373.2015.1076537.
Stone-Romero, E. F., & Rosopa, P. J. (2008). The relative validity of inferences about mediation as a function of research design characteristics. Organizational Research Methods, 11(2), 326–352. https://doi.org/10.1177/1094428107300342.
Tuma, N. B., & Hannan, M. T. (1984). Social dynamics models and methods. Saint Louis, US: Elsevier.
Watson, D., Pennebaker, J. W., & Folger, R. (1986). Beyond negative affectivity: Measuring stress and satisfaction in the workplace. Journal of Organizational Behavior Management, 8(2), 141–157. https://doi.org/10.1300/J075v08n02_09.
Woodward, J. (2003). Making things happen: A theory of causal explanation. Oxford: New York City.
Woodward, J. (2017). Scientific explanation. In E. N. Zalta (Ed.), Stanford encyclopedia of philosophy. Retrieved from https://plato.stanford.edu/archives/fall2017/entries/scientific-explanation. Accessed 28 Dec 2018.
Zapf, D., Dormann, C., & Frese, M. (1996). Longitudinal studies in organizational stress research: A review of the literature with reference to methodological issues. Journal of Occupational Health Psychology, 1(2), 145–169. https://doi.org/10.1037/1076-89126.96.36.199.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Spector, P.E. Do Not Cross Me: Optimizing the Use of Cross-Sectional Designs. J Bus Psychol 34, 125–137 (2019). https://doi.org/10.1007/s10869-018-09613-8
- Causal inference
- Cross-sectional design
- Longitudinal design
- Method variance
- Philosophy of science
- Research design
- Research methodology