Column-transformation functions for Xpose 4
Source:R/add.absval.R
, R/add.dichot.R
, R/add.exp.R
, and 2 more
add_transformed_columns.Rd
These functions transform existing Xpose 4 data columns, adding new columns.
Usage
add.absval(object, listall = TRUE, classic = FALSE)
add.dichot(object, listall = TRUE, classic = FALSE)
add.exp(object, listall = TRUE, classic = FALSE)
add.log(object, listall = TRUE, classic = FALSE)
add.tad(object, classic = FALSE)
Arguments
- object
An
xpose.data
object.- listall
A logical operator specifying whether the items in the database should be listed.
- classic
A logical operator specifying whether the function should assume the classic menu system. This is an internal option and need never be called from the command line.
Value
An xpose.data
object (classic == FALSE) or null
(classic == TRUE).
Details
These functions may be used to create new data columns within the Xpose data object by transforming existing ones.
Functions
add.absval()
: Create a column containing the absolute values of data in another column.add.dichot()
: Create a categorical data column based on a continuous data columnadd.exp()
: Create an exponentiated version of an existing variableadd.log()
: Create a log transformation of an existing variableadd.tad()
: Create a time-after-dose (TAD) data item based upon the dose and time variables in the dataset.
See also
Other data functions:
change_graphical_parameters
,
change_misc_parameters
,
compute.cwres()
,
data.checkout()
,
data_extract_or_assign
,
db.names()
,
export.graph.par()
,
export.variable.definitions()
,
import.graph.par()
,
import.variable.definitions()
,
make.sb.data()
,
nsim()
,
par_cov_summary
,
read.TTE.sim.data()
,
read.nm.tables()
,
read_NM_output
,
read_nm_table()
,
simprazExample()
,
tabulate.parameters()
,
xlabel()
,
xpose.data
,
xpose.print()
,
xpose4-package
,
xsubset()
Examples
if (FALSE) {
## xpdb5 is an Xpose data object
## We expect to find the required NONMEM run and table files for run
## 5 in the current working directory
xpdb5 <- xpose.data(5)
## Create a column containing the absolute values of data in another
## column
add.absval(xpdb5)
## Create a categorical data column based on a continuous data column,
## and do not list variables
add.dichot(xpdb5, listall = FALSE)
## Create a column containing the exponentiated values of data in
## another column
add.exp(xpdb5)
## Create a column containing log-transformations of data in another
## column
add.log(xpdb5)
## Create a time-after-dose column
add.tad(xpdb5)
}