Bland-Altman plot

Bland-Altman plot (Tukey mean-difference plot) is a simple method for analyzing the agreement between two different analysis methods or interobserver variability. Comparison can even be done pixel-by-pixel for parametric images.

Bland-Altman plot is made by plotting the average of the two values to be compared to the x axis, and the difference to the y axis.

Bland-Altman plots are also simple to interpret:

  1. If there is (significant) bias, is it clinically important?
  2. If there is a trend, then in what direction it would affect your results?
  3. Is variance increasing with increasing average?

Standard deviation (SD) of the differences between the two methods can also be calculated, and further used to describe the limits of agreement, as the mean ± 1.96×SD.

The original Bland-Altman plot cannot be used to assess agreement between two measurement methods in a test-retest setting; however, modification of the method is applicable (Bland & Altman, 1999).


See also:


Literature

Altman DG, Bland JM. Measurement in medicine: the analysis of method comparison studies. Statistician 1983; 32: 307-317. JSTOR. doi: 10.2307/2987937.

Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986; 327(8476): 307-310. doi: 10.1016/S0140-6736(86)90837-8. Republished 2010 in 10.1016/j.ijnurstu.2009.10.001.

Bland JM, Altman DG. Measuring agreement in method comparison studies. Stat Methods Med Res. 1999; 8: 135-160. doi: 10.1177/096228029900800204.

Choudhary PK, Nagaraja HN: Measuring Agreement: Models, Methods, and Applications. Wiley, 2018. ISBN 978-1-118-07858-7.

de Vet HCW, Terwee CB, Mokkink LB, Knol DL (eds.): Measurement in Medicine: A Practical Guide. Cambridge University Press, 2011. ISBN: 9780521118200.

Eksborg S. Evaluation of method-comparison data. Clin Chem. 1981; 27(7): 1311-1312.

Gerke O, Vilstrup MH, Segtnan EA, Halekoh U, Høilund-Carsen PF. How to assess intra- and inter-observer agreement with quantitative PET using variance component analysis: a proposal for standardisation. BMC Med Imaging 2016; 16:54. doi: 10.1186/s12880-016-0159-3.

Lin L, Hedayat AS, Wu W: Statistical Tools for Measuring Agreement. Springer, 2012. doi: 10.1007/978-1-4614-0562-7.

Ludbrook J. Statistical techniques for comparing measurers and methods of measurement: a critical review. Clin Exp Pharmacol Physiol. 2002; 29(7): 527-536. doi: 10.1046/j.1440-1681.2002.03686.x.

Ludbrook J. Confidence in Altman-Bland plots: a critical review of the method of differences. Clin Exp Pharmacol Physiol. 2010; 37(2): 143-149. doi: 10.1111/j.1440-1681.2009.05288.x.

Nesterov SV, Han C, Mäki M, Kajander S, Naum AG, Helenius H, Lisinen I, Ukkonen H, Pietilä M, Joutsiniemi E, Knuuti J. Myocardial perfusion quantitation with 15O-labelled water PET: high reproducibility of the new cardiac analysis software (Carimas). Eur J Nucl Med Mol Imaging. 2009; 36(10): 1594-1602. doi: 10.1007/s00259-009-1143-8.

van Stralen KJ, Jager KJ, Zoccali C, Dekker FW. Agreement between methods. Kidney Int. 2008; 74: 1116-1120. doi: 10.1038/ki.2008.306.

Watson PF, Petrie A. Method agreement analysis: a review of correct methodology. Theriogenol. 2010; 73: 1167-1179. doi: 10.1016/j.theriogenology.2010.01.003.



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Updated at: 2018-12-21
Created at: 2014-05-23
Written by: Vesa Oikonen