measure_compare() 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.
measure_compare(
data,
new = "y1",
ref = "y2",
id = "id",
nb_simul = 1000,
if_value = NULL
)The function returns a list with the following items:
models: a list of models fitted in estimation procedure
data: the original data frame with renamed columns and
additional computed data
sim_params: estimated model coefficients used afterward
nb_simul: the number of simulations used for confidence bands
simulations
bias: differential and proportional biases for new method and the
associated 95 percent confidence intervals
methods: a list of methods names provided by the user
a required data frame containing the identification number of the
subject (id), the measurement values from the new method (y1) and
those from the reference method (y2).
an optional string. The column name containing the measurements of the new measurement method.
an optional string. The column name containing the measurements of the reference method (at least two measurements per subject).
an optional string. The column name containing the subject identification numbers.
an optional number. The number of simulations used for simultaneous confidence bands.
an optional number. Restrict the study to observed
measurement greater than the provided value, i.e., y1 >= if_value && y2 >= if_value.
# \donttest{
### Load the data
data(data1)
### Analysis
measure_model <- measure_compare(data1, nb_simul=100)# }
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