addCovariate.Rd
Add a continuous, categorical, or occasion covariate to model object and set covariate effect on structural parameters.
addCovariate(
.Object,
covariate,
effect = NULL,
type = c("Continuous", "Categorical", "Occasion"),
direction = c("Forward", "Interpolate", "Backward"),
option = c("Yes", "PlusOne", "No"),
center = NULL,
centerValue = NULL,
levels = NULL,
labels = NULL,
isDiagonal = TRUE,
values = NULL,
isPositive = TRUE
)
Model object
Name of covariate. If the involved model has columns
mapped (i.e. model with columnMap = TRUE
) use named character if the name
of the covariate is different from the corresponding column in the input
dataset, for example, covariate = c(BW = "BodyWeight")
, where BW
denotes the name of the covariate, and "BodyWeight"
is the name of the
corresponding column in the input dataset.
Name of structural parameter(s) on which the covariate
has an effect. Specify effect
as character or character vector if the
covariate has an effect on multiple structural parameters.
Type of covariate. Options are "Continuous"
,
"Categorical"
, "Occasion"
.
Direction of missing values propagation (if no covariate
value is given). Options are "Forward"
, "Interpolate"
, "Backward"
,
where "Interpolate"
is only applicable to type = "Continuous"
.
Options are "Yes"
, "PlusOne"
, or "No"
, where
option = "No"
will remove the covariate effect from the specified
structural parameter(s), but retain the covariate in the model. Note:
option = "PlusOne"
is only applicable to continuous and categorical
covariates in the case where structural parameters have style = "LogNormal"
. Multiple options are not supported (i.e. all covariate
effects in the call are supposed to have the same option
. If different
option
s are required for different covariate effects, sequential calls of
current method could be done.
Centering method. Options are "Mean"
, "Median"
,
"Value"
or "None"
. Only applicable to covariate type = "Continuous"
.
Must include argument centerValue
if center = "Value"
.
Value used to center covariate. Only applicable if
argument center = "Value"
and type = "Continuous"
.
Unique values of categorical or occasion covariate. Only
applicable to covariate type = "Categorical"
or type = "Occasion"
.
Label names (in the same order as levels) for unique levels of
categorical or occasion covariate in data. Only applicable to covariate
type = "Categorical"
or type = "Occasion"
where its corresponding
column in the input dataset has character type.
Set to FALSE
if inter-occasion covariance matrix is not
diagonal matrix. Only applicable to covariate type = "Occasion"
.
Initial values for the diagonal elements of the inter-occasion
covariance matrix (if isDiagonal = TRUE
) or initial values for the lower
triangular elements (including diagonal elements) of inter-occasion
covariance matrix (if isDiagonal = FALSE
) in a row-wise order. Only
applicable for covariate type = "Occasion"
.
Set to FALSE
if covariate contains negative values.
Only applicable to covariate type = "Continuous"
.
The following relationships are applicable for covariates:
direction = "Forward"
is equivalent to PML code 'fcovariate(CovName)';
direction = "Backward"
is equivalent to PML code 'covariate(CovName)';
direction = "Interpolate"
is equivalent to PML code 'interpolate(CovName)'.
If the structural parameter has style = "LogNormal"
, the options are
reflected in PML code as follows:
option = "Yes"
is equivalent to
stparm(V = tvV * wt^dVdwt * exp(dVdsex1*(sex==1)) * exp(nV))
;
option = "PlusOne
is equivalent to
stparm(V = tvV * (1+wt*dVdwt) * (1+dVdsex1*(sex==1)) * exp(nV))
.
model <- pkmodel(
numCompartments = 2,
data = pkData,
ID = "Subject",
Time = "Act_Time",
A1 = "Amount",
CObs = "Conc"
)
# Add Gender covariate of type categorical
model <- addCovariate(model,
covariate = "Gender",
type = "Categorical",
effect = c("V2", "Cl2"),
levels = c(0, 1),
labels = c("Female", "Male")
)
# Add BodyWeight covariate of type continuous
model <- addCovariate(model,
covariate = "BodyWeight",
type = "Continuous",
direction = "Backward",
center = "Mean",
effect = c("V", "Cl")
)