Skip to main content

Advertisement

Log in

A primer on common statistical errors in clinical ophthalmology

  • REVIEW ARTICLE
  • Published:
Documenta Ophthalmologica Aims and scope Submit manuscript

Abstract

Although biomedical statistics is part of any scientific curriculum, a review of the current scientific literature indicates that statistical data analysis is an area that frequently needs improvement. To address this, we here cover some of the most common problems in statistical analysis, with an emphasis on an intuitive, tutorial approach rather than a rigorous, proof-based one. The topics covered in this manuscript are whether to enter eyes or patients into the analysis, issues related to multiple testing, pitfalls surrounding the correlation coefficient (causation, insensitivity to patterns, range confounding, unsuitability for method comparisons), and when to use standard deviation (SD) versus standard error of the mean (SEM) “antennas” on graphs.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Strasak AM, Zaman Q, Pfeiffer KP, Gobel G, Ulmer H (2007) Statistical errors in medical research—a review of common pitfalls. Swiss Med Wkly 137:44–49

    PubMed  Google Scholar 

  2. Murdoch IE, Morris SS, Cousens SN (1998) People and eyes: statistical approaches in ophthalmology. Br J Ophthalmol 82:971–973

    Article  CAS  PubMed  Google Scholar 

  3. Newcombe RG, Duff GR (1987) Eyes or patients? Traps for the unwary in the statistical analysis of ophthalmological studies. Br J Ophthalmol 71:645–646

    Article  CAS  PubMed  Google Scholar 

  4. Rosner B (1984) Multivariate methods in opthalmology with application to other paired data situations. Biometrics 40:1025–1036

    Article  CAS  PubMed  Google Scholar 

  5. Liang KY, Zeger SL (1986) Longitudinal data analysis using generalized linear models. Biometrika 73:13–22

    Article  Google Scholar 

  6. Katz J, Zeger S, Liang KY (1994) Appropriate statistical methods to account for similarities in binary outcomes between fellow eyes. Invest Ophthalmol Vis Sci 35:2461–2465

    CAS  PubMed  Google Scholar 

  7. Glynn RJ, Rosner B (1992) Accounting for the correlation between fellow eyes in regression analysis. Arch Ophthalmol 110:381–387

    CAS  PubMed  Google Scholar 

  8. Holm S (1979) A simple sequentially rejective multiple test procedure. Scand J Stat 6:65–70

    Google Scholar 

  9. Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310

    CAS  PubMed  Google Scholar 

  10. Cumming G, Finch S (2005) Inference by eye: confidence intervals and how to read pictures of data. Am Psychol 60:170–180

    Article  PubMed  Google Scholar 

  11. Cumming G, Fidler F, Vaux DL (2007) Error bars in experimental biology. J Cell Biol 177:7–11

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

This work was supported by a grant from the Foundation Fighting Blindness, Columbia, Maryland and a grant from the Allene Reuss Memorial Trust, New York, New York.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Karen Holopigian.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Holopigian, K., Bach, M. A primer on common statistical errors in clinical ophthalmology. Doc Ophthalmol 121, 215–222 (2010). https://doi.org/10.1007/s10633-010-9249-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10633-010-9249-7

Keywords

Navigation