Contents
How to measure agreement between two methods?
When two instruments or techniques are used to measure the same variable on a continuous scale, the Bland–Altman plots can be used to estimate agreement. This plot is a scatter plot of the difference between the two measurements (Y-axis) against the average of the two measurements (X-axis).
Which test is appropriate coefficient of measuring agreement?
correlation coefficient
The old favorite for measuring agreement is the correlation coefficient (r) [4]. However, this is obviously inappropriate as correlation only measures the strength of linear association between variables.
What is a good percentage agreement?
If it’s a sports competition, you might accept a 60% rater agreement to decide a winner. However, if you’re looking at data from cancer specialists deciding on a course of treatment, you’ll want a much higher agreement — above 90%. In general, above 75% is considered acceptable for most fields.
How to measure the agreement between two meters?
Only the first measurement by each method is used to illustrate the comparison of methods, the second measurement being used in the study of repeatability. The first step is to plot the data and draw the line of equality on which all points would lie if the two meters gave exactly the same reading every time (fig 1).
What are statistical methods for assessing agreement between two methods?
Bland JM, Altman DG. (1986). Statistical methods for assessing agreement between two methods of clinical measurement. Lancet, i, 307-310. It was reprinted with a small numerical correction (included in this version) by Biochimica Clinica, as:
What is the difference between correlation and agreement?
Correlation refers to the presence of a relationship between two different variables, whereas agreement looks at the concordance between two measurements of one variable. Two sets of observations, which are highly correlated, may have poor agreement; however, if the two sets of values agree, they will surely be highly correlated.
How to find the correlation between two measurements?
The correlation would be 1.0, but the two measurements would not agree — we could not mix fat thicknesses obtained by the two methods, since one is twice the other. (3) Correlation depends on the range of the true quantity in the sample. If this is wide, the correlation will be greater than if it is narrow.