Calculates Lin's (1989, 2000) concordance correlation coefficient for agreement on a continuous measure.
epi.ccc(x, y, ci = "z-transform", conf.level = 0.95, rep.measure = FALSE,
subjectid)A list containing the following:
the concordance correlation coefficient.
the scale shift.
the location shift.
a bias correction factor that measures how far the best-fit line deviates from a line at 45 degrees. No deviation from the 45 degree line occurs when C.b = 1. See Lin (1989, page 258).
a data frame with two columns: mean the mean of each pair of measurements, delta vector y minus vector x.
a data frame listing the average difference between the two sets of measurements, the standard deviation of the difference between the two sets of measurements and the lower and upper confidence limits of the difference between the two sets of measurements. If rep.measure == TRUE the confidence interval of the difference is adjusted to account for repeated observations across individual subjects.
a count of the number of measurement pairs ignored due to missingness.
a vector, representing the first set of measurements.
a vector, representing the second set of measurements.
a character string, indicating the method to be used. Options are z-transform or asymptotic.
magnitude of the returned confidence interval. Must be a single number between 0 and 1.
logical. If TRUE there are repeated observations across subject.
a factor providing details of the observer identifier if rep.measure == TRUE.
Computes Lin's (1989, 2000) concordance correlation coefficient for agreement on a continuous measure obtained by two methods. The concordance correlation coefficient combines measures of both precision and accuracy to determine how far the observed data deviate from the line of perfect concordance (that is, the line at 45 degrees on a square scatter plot). Lin's coefficient increases in value as a function of the nearness of the data's reduced major axis to the line of perfect concordance (the accuracy of the data) and of the tightness of the data about its reduced major axis (the precision of the data).
Both x and y values need to be present for a measurement pair to be included in the analysis. If either or both values are missing (i.e., coded NA) then the measurement pair is deleted before analysis.
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epi.occc