biomarker | R Documentation |
biomarker(xLevel, model, samples, ...)
## S4 method for signature 'integer,DualEndpoint,Samples'
biomarker(xLevel, model, samples, ...)
xLevel |
( |
model |
( |
samples |
( |
... |
not used. |
This function simply returns a specific columns (with the indices equal
to xLevel
) of the biomarker samples matrix, which is included in the the
samples
object.
The biomarker levels.
biomarker(xLevel = integer, model = DualEndpoint, samples = Samples)
:
# Create the data.
my_data <- DataDual(
x = c(0.1, 0.5, 1.5, 3, 6, 10, 10, 10, 20, 20, 20, 40, 40, 40, 50, 50, 50),
y = c(0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1),
ID = 1:17,
cohort = c(1L, 2L, 3L, 4L, 5L, 6L, 6L, 6L, 7L, 7L, 7L, 8L, 8L, 8L, 9L, 9L, 9L),
w = c(
0.31, 0.42, 0.59, 0.45, 0.6, 0.7, 0.55, 0.6, 0.52, 0.54,
0.56, 0.43, 0.41, 0.39, 0.34, 0.38, 0.21
),
doseGrid = c(0.1, 0.5, 1.5, 3, 6, seq(from = 10, to = 80, by = 2))
)
# Initialize the Dual-Endpoint model (in this case RW1).
my_model <- DualEndpointRW(
mean = c(0, 1),
cov = matrix(c(1, 0, 0, 1), nrow = 2),
sigma2betaW = 0.01,
sigma2W = c(a = 0.1, b = 0.1),
rho = c(a = 1, b = 1),
rw1 = TRUE
)
# Set-up some MCMC parameters and generate samples from the posterior.
my_options <- McmcOptions(
burnin = 100,
step = 2,
samples = 500
)
my_samples <- mcmc(my_data, my_model, my_options)
# Obtain the biomarker levels (samples) for the second dose from the dose grid,
# which is 0.5.
biomarker(
xLevel = 2L,
model = my_model,
samples = my_samples
)
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