Bland-Altman analysis: A paradigm to understand correlation and agreement

Doğan, Nurettın Özgür

doi:10.1016/j.tjem.2018.09.001

Cited by 192 publications

(118 citation statements)

References 16 publications

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“…0.0036, 0,0022, 0.0023, 0.0021 and 0.0015 at 1-month, 3-month, 6-month, 12-month and 24-month time scales respectively), hence indicated good agreement between SPI and SPEI at all time scales. Moreover, the test results agreed with [82] which stated that good agreement can be expected if the scattering of points is diminished, and points lie relatively close to the line which represents mean bias. This proved that there existed a good level of agreement since most of the scattering points lie within the upper and lower limits of agreement close to the mean difference of each time scale (see Fig.…”

Section: Degree Of Agreement Between Spi and Speisupporting

confidence: 79%

“…This is mainly due to the fact that two methods might have a perfect positive or negative correlation but with no agreement between them. This was reinforced by [54,82], which recommended against the use of correlation as a method for assessing the comparability between methods. Hence, in this study, the PCC results strictly indicate the direction and strength of the linear relationship between SPI and SPEI not the degree of agreement between them.…”

Section: Linear Relationship Between Spi and Speimentioning

confidence: 99%

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Comparative analyses of SPI and SPEI as drought assessment tools in Tigray Region, Northern Ethiopia

2019

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Standard Precipitation Index (SPI) and, its variant, Standard Precipitation and Evapotranspiration Index (SPEI) are among the most commonly used drought assessment indices worldwide. SPI uses precipitation as its only input to assess drought. Unlike SPI, SPEI uses both precipitation and temperature, thereby considering the influence of global warming to some extent. Assessments of performance between SPI and SPEI is well addressed. However, no adequate literature was found on the assessment of the degree of agreement between SPI and SPEI at different time scales. Hence, this research focused on examining the level of agreement between SPI and SPEI as drought assessment tools at 1-month, 3-month, 6-month, 12-month and 24-month time scales. The test of agreement between SPI and SPEI was conducted using Cohen's Kappa statistics and the Bland-Altman method. Gridded monthly precipitation and temperature Climatic Research Unit time-series data version 4.01 were used to calculate SPI and SPEI for the period 1901 to 2016. The results of Cohen's Kappa statistics indicate that there existed a fair degree of agreement between SPI and SPEI at all time scales. A positive linear correlation (r > 0.7, p < 0.001) was also observed between SPI and SPEI ratings at all time scales. Small mean difference (bias) in the Bland and Altman analyses result indicated for the presence of agreement between the assessment tools. This study has found that there is an acceptable level of agreement between SPI and SPEI ratings in the study area, at all timescales.

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Section: Degree Of Agreement Between Spi and Speisupporting

confidence: 79%

Section: Linear Relationship Between Spi and Speimentioning

confidence: 99%

Comparative analyses of SPI and SPEI as drought assessment tools in Tigray Region, Northern Ethiopia

2019

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“…The primary finding of this study was that measured mitochondrial rate constants were equivalent (absence of a meaningful effect) when calculated from a reduced number of data points (Mito6) compared to a full set of data points (Mito22). The conclusions were based on equivalency testing (Lakens, 2017) and Bland-Altman analysis (Altman and Bland, 1983;Dogan, 2018). The results of this study therefore support the validity and repeatability of the Mito6 protocol.…”

Section: Discussionsupporting

confidence: 67%

“…This testing evaluated the mean difference between the two analyses (Mito22 and Mito6/Mito5 * ) and determined the 90% confidence interval for the mean difference and the equivalence bounds which was assumed to be 5% of the mean rate constant values. This approach provides similar analysis outcomes to that for Bland-Altman analyses (Altman and Bland, 1983;Dogan, 2018). Bland-Altman analysis was also performed and the slope and R 2 -values for the rate constants of the data: (Mito22-Mito6)/(Mito22 + Mito6)/2, was performed to evaluate potential changes in agreement with the rate constants and magnitude of the rate constant (Altman and Bland, 1983).…”

Section: Data Analysis and Statisticsmentioning

confidence: 99%

Near Infrared Spectroscopy Measurements of Mitochondrial Capacity Using Partial Recovery Curves

Sumner

Beard

et al. 2020

Front. Physiol.

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Background: Near-infrared spectroscopy (NIRS) has been used to measure muscle mitochondrial capacity (mVO 2 max) as the recovery rate constant of muscle metabolism after exercise. The current method requires as many as 50 short ischemic occlusions to generate two recovery rate constants. Purpose: To determine the validity and repeatability of using a 6-occlusion protocol versus one with 22 occlusions to measure muscle mitochondrial capacity. The order effect of performing multiple Mito6 test was also evaluated. Method: In two independent data sets (bicep n = 7, forearm A n = 23), recovery curves were analyzed independently using both the 6 and 22 occlusion methods. A third data set (forearm B n = 16) was generated on the forearm muscles of healthy subjects using four 6-occlusion tests performed in succession. Recovery rate constants were generated using a MATLAB routine. Results: When calculated from the same data set, the recovery rate constants were not significantly different between the 22 occlusion and 6 occlusion methods for the bicep (1.43 ± 0.33 min −1 , 1.43 ± 0.35 min −1 , p = 0.81) and the forearm A (1.97 ± 0.40 min −1 , 1.97 ± 0.43 min −1 , p = 0.90). Equivalence testing showed that the mean difference was not different than zero and the 90% confidence intervals were within 5% of the average rate constant. This was true for the Mito6 and the Mito5 * approaches. Bland-Altman analysis showed a slope of 0.21 min −1 and an r of 0.045 for the bicep dataset and a slope of −0.01 min −1 and an r of 0.045 for the forearm A dataset. When performing the four 6-occlusion tests; recovery rate constants showed no order effects (1.50 ± 0.51 min −1 , 1.42 ± 0.54 min −1 , 1.26 ± 0.41 min −1 , 1.29 ± 0.47 min −1 , P > 0.05). Conclusion: The Mito6 analysis is a valid and repeatable approach to measure mitochondrial capacity. The Mito6 protocol used fewer ischemic occlusion periods and multiple tests could be performed in succession in less time, increasing the practicality of the NIRS mitochondrial capacity test. There were no order effects for the rate constants of four repeated 6-occlusion tests of mitochondrial capacity, supporting the use of multiple tests to improve accuracy.

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“…As can be seen from this example, when evaluating the reliability of the two test measurement results, it is wrong to make conclusions only by looking at the correlation coefficient. In this case, the test that should be preferred is the Bland-Altman analysis, and a compatibility assessment should be made along with the correlation [2]. In our study, which presented the highest number of cases related to BGA and LAA compatibility in the literature, 31060 patient data were examined and although moderate correlation was found for sodium and potassium, and strong correlation was found for hemoglobin, hematocrit and glucose, mean differences were not within acceptable limits for any test.…”

Section: To the Editormentioning

confidence: 99%

Blood gas analysis is not reliable for serum electrolytes and can lead to wrong clinical decisions

2020

Ann Clin Anal Med

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Bland-Altman analysis: A paradigm to understand correlation and agreement

Cited by 192 publications

References 16 publications

Comparative analyses of SPI and SPEI as drought assessment tools in Tigray Region, Northern Ethiopia

Comparative analyses of SPI and SPEI as drought assessment tools in Tigray Region, Northern Ethiopia

Near Infrared Spectroscopy Measurements of Mitochondrial Capacity Using Partial Recovery Curves

Blood gas analysis is not reliable for serum electrolytes and can lead to wrong clinical decisions

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