Description Usage Arguments Details Value Author(s) Examples
View source: R/measure_compare.R
This function implements the methodology reported in the paper: Taffé P. Effective plots to assess bias and precision in method comparison studies. Stat Methods Med Res 2018;27:1650-1660. Other relevant references: Taffé P, Peng M, Stagg V, Williamson T. Biasplot: A package to effective plots to assess bias and precision in method comparison studies. Stata J 2017;17:208-221. Taffé P, Peng M, Stagg V, Williamson T. MethodCompare: An R package to assess bias and precision in method comparison studies. Stat Methods Med Res 2019;28:2557-2565. Taffé P, Halfon P, Halfon M. A new statistical methodology to assess bias and precision overcomes the defects of the Bland & Altman method. J Clin Epidemiol 2020;124:1-7. Taffé P. Assessing bias, precision, and agreement in method comparison studies. Stat Methods Med Res 2020;29:778-796. Taffé P. When can the Bland-Altman limits of agreement method be used and when it should not be used. J Clin Epidemiol 2021; 137:176-181.
1 | measure_compare(data, new = "y1", Ref = "y2", ID = "id")
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data |
a dataframe containing the identification number of the subject (id), the measurement values from the new measurement method (y1) and those from the reference method). |
new |
specify the variable name or location of the new measurement method |
Ref |
specify the variable name or location of the reference standard |
ID |
specify the variable name for location of the subject identification number |
This functions implements the new estimation procedure to assess bias and precision of a new measurement method with respect to a reference standard, as well as Bland & Altman's limits of agreement extended to the setting of possibly heteroscedastic variance of the measurement errors.
The function returns a list with the following items:
Bias: differential and proportional bias for new method and the associated 95 percent confidence intervals
Models: list of models fitted in estimation procedure
Ref: a data frame containing the various variables used to compute the bias and precision plots, as well the smooth standard errors estimates of the reference standard
New: a data frame containing the various variables used to compute the bias and precision plots, as well the smooth standard errors estimates of the new measurement method
Mingkai Peng & Patrick Taffé
1 2 3 4 | ### Load the data
data(data1)
### Analysis
measure_model <- measure_compare(data1)
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Loading required package: nlme
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