Functions changing miscellaneous parameter settings in Xpose 4

These functions allow viewing and changing of settings relating to subsets, categorical threshold values, documentation and numbers indicating missing data values.

Usage

change.cat.cont(
  object,
  listall = TRUE,
  classic = FALSE,
  to.cat.vec = NULL,
  to.cont.vec = NULL,
  change.type.vec = NULL,
  ...
)

change.cat.cont(
  object,
  listall = TRUE,
  classic = FALSE,
  to.cat.vec = NULL,
  to.cont.vec = NULL,
  ...
) <- value

change.cat.levels(object, classic = FALSE, cat.limit = NULL, ...)

change.cat.levels(object, classic = FALSE, ...) <- value

change.dv.cat.levels(object, classic = FALSE, dv.cat.limit = NULL, ...)

change.dv.cat.levels(object, classic = FALSE, ...) <- value

change.miss(object, classic = FALSE)

change.subset(object, classic = FALSE)

get.doc(object, classic = FALSE)

set.doc(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.
to.cat.vec: A vector of strings specifying the names of the categorical variables that should be transformed to continuous.
to.cont.vec: A vector of strings specifying the names of the continuous variables that should be transformed to categorical.
change.type.vec: A vector of strings specifying the names of the variables that should be transformed to/from continuous/categorical.
...: arguments passed to other functions.
value: This is the value that will be replaced in the xpose data object object. value is used in the “replacement function” version of these functions. That is the form where we have function.name(object) <- value. If value is NULL then the functions prompt the user for a value. For change.cat.levels, value is the categorical limit cat.limit. For change.dv.cat.levels, value is the DV categorical limit dv.cat.limit. For change.cat.cont, value is the change.type.vec. See the examples below.
cat.limit: The limit for which we treat a list of values as categorical. If there are cat.limit or less unique values then the list is treated as categorical.
dv.cat.limit: The limit for which we treat DV as categorical. If there are dv.cat.limit or less unique dv values then dv is treated as categorical.

Value

An xpose.data object, except get.doc, which returns the value of object@Doc.

Functions

change.cat.cont(): allows interchange between categorical and continuous data formats within the Xpose database. This in turn affects how plots are drawn.
change.cat.cont( object, listall = TRUE, classic = FALSE, to.cat.vec = NULL, to.cont.vec = NULL, ... ) <- value: allows interchange between categorical and continuous data formats within the Xpose database. This in turn affects how plots are drawn.
change.cat.levels(): change settings for the number of unique data values required in a variable in order to define it as continuous for ordinary variables.
change.cat.levels(object, classic = FALSE, ...) <- value: change settings for the number of unique data values required in a variable in order to define it as continuous for ordinary variables.
change.dv.cat.levels(): change settings for the number of unique data values required in a variable in order to define it as continuous for the dependent variable.
change.dv.cat.levels(object, classic = FALSE, ...) <- value: change settings for the number of unique data values required in a variable in order to define it as continuous for the dependent variable.
change.miss(): change the value to use as 'missing'.
change.subset(): is used for setting the data item's subset field. To specify a subset of the data to process, you use the variable names and the regular R selection operators. To combine a subset over two or more variables, the selection expressions for the two variables are combined using R's unary logical operators.

The variable names are those that are specified in the NONMEM table files (e.g. PRED, TIME, SEX).

The selection operators are: == (equal) != (not equal) || (or) > (greater than) < (less than)

For example, to specify that TIME less than 24 should be processed, you type the expression: TIME < 24.

The unary logical operators are: & (and) | (or)

For example, to specify TIME less than 24 and males (SEX equal to 1), you type the expression: TIME < 24 & SEX == 1

This subset selection scheme works on all variables, including ID numbers.

The subset selection is not entirely stable. For example, there is no check that the user enters a valid expression, nor that the user specifies existing variable names. An erroneous expression will not become evident until a plot is attempted and the expression takes effect.
get.doc(): get the documentation field in the Xpose data object.
set.doc(): set the documentation field in the Xpose data object.

Author

Andrew Hooker, Niclas Jonsson & Justin Wilkins

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)

## Change default subset
xpdb5 <- change.subset(xpdb5)

## Set documentation field
xpdb5 <- set.doc(xpdb5)
## View it
view.doc(xpdb5)

## change the categorical limit for the dv variable
change.dv.cat.levels(xpdb5) <- 10

## change the categorical limit for non DV variables
change.cat.levels(xpdb5) <- 2
## or
xpdb5 <- change.cat.levels(xpdb5,cat.levels=2)

## chnage variables from categorical to continuous
xpdb5 <- change.cat.cont(xpdb5,to.cat.vec=c("AGE"),to.cont.vec=c("SEX"))
xpdb5 <- change.cat.cont(xpdb5,change.type.vec=c("AGE","SEX"))
change.cat.cont(xpdb5) <- c("AGE","SEX")
}