| 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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