planModPrepare {MCPModGeneral} | R Documentation |
Return the S Matrix for a Theoretical DR-Curve
Description
This function is useful for several DoseFinding
functions, but
particular for planMod
. Given the true dose-response curve at
specified doses, this function will calculate and return the S matrix
associated with the specified distribution. If an object of class Mods
is provided in the models
argument, then a list of S matrices will be
returned.
Usage
planModPrepare(
nSample,
family = c("negative binomial", "binomial", "poisson"),
link = c("log", "logit", "sqrt", "probit", "cauchit", "cloglog", "identity",
"risk ratio", "log risk ratio"),
modelPar = NULL,
theoResp = NULL,
doses = NULL,
Ntype = c("arm", "total", "actual"),
alRatio = NULL,
placEff = NULL,
models = NULL,
verbose = FALSE,
offset = NULL
)
Arguments
nSample |
An integer if |
family |
A character string containing the error distribution to be used in the model. |
link |
A character string for the model link function. |
modelPar |
A numeric vector containing the additional parameters for the family argument. If the family is negative binomial, the dispersion parameter should be supplied. If the family is binomial, no model parameter should be supplied. |
theoResp |
A numerical vector of theoretical response values, on the transformed scale (e.g. on the log-scale for the negative binomial family). This should be the same length as the doses argument. |
doses |
A numerical vector of doses, corresponding to the theoretical response values provided. |
Ntype |
One of 'arm', 'total', or 'actual'. See documentation for
|
alRatio |
A numeric vector specifying the ratios between the patient allocation for the specified doses. |
placEff |
A numeric value of the placebo effect. This is needed only when the link is risk ratio. |
models |
Instead of supplying a theoretical dose-response curve and
doses, an object of class |
verbose |
A logical specifying whether the patient allocation should be printed, in addition to the results. |
offset |
A positive numeric value specifying the offset term for the negative binomial distribution. If offset = NULL (the default), then the offset has no effect. Theoretically, the offset should be a numeric vector the same length as the number of observations, but for planning purposes, it is unlikely to know the individual offsets in advance. |
Value
A numeric S matrix, or a list S matrices, for each model is
models
.
Examples
dose.vec = c(0, 5, 10, 20, 30, 40)
models.full = Mods(doses = dose.vec, linear = NULL,
sigEmax = rbind(c(9, 2), c(6, 3)),
emax = 0.8,
quadratic = -0.02,
placEff = 0, maxEff = 2)
planModPrepare(30, 'negative binomial', 'log', 0.3, getResp(models.full)[,3],
dose.vec, 'arm')