createPcAux: Extract principal component scores for use as the auxiliary...

In dsquire/PcAux: Principle Components Auxiliary Variables

Extract principal component scores for use as the auxiliary variables in a principled missing data analysis as described by Howard, Rhemtulla, and Little (2015).

Description

Extract principal component scores for use as the auxiliary variables in a principled missing data analysis as described by Howard, Rhemtulla, and Little (2015).

Usage

createPcAux(
  pcAuxData,
  nComps,
  interactType = 0L,
  maxPolyPow = 1L,
  simMode = FALSE,
  seed = NULL,
  verbose = 2L,
  doImputation = TRUE,
  castData = !doImputation,
  control,
  micemethods = c("norm", "polr", "polyreg", "logreg"),
  ...
)

Arguments

pcAuxData	An object of class PcAuxData returned from prepData.
nComps	A two-element, numeric vector giving the number of linear and nonlinear, re- spectively, component scores to extract. See the Details section for more infor- mation.
interactType	An integer code indicating which method is used to incorporate interactions into the initial, single imputation model. See the Details section for more informa- tion. Defaults to interactType = 1L.
maxPolyPow	An integer giving the maximum power used when constructing the polynomial terms. Setting maxPolyPow = 1L has the effect of excluding any polynomial terms from the imputation model. Defaults to maxPolyPow = 3L.
simMode	A logical switch turning ’Simulation Mode’ on or off. In Simulation Mode all of the automatic data checks will be suppressed. This mode is intended for use when pcAux is being called as part of a Monte Carlo simulation study in which the data properties are well-known by the user. This mode should not be used for ’real-world’ data analysis. Defaults to simMode = FALSE.
seed	An optional integer used to seed the random number generator used by the im- putation algorithm. Defaults to seed = NULL which leaves the default random number generator unaltered.
verbose	An integer code in 0, 1, 2 defining the verbosity of output printed to the screen. verbose = 0prints no output; verbose = 1prints all output except for the mes- sages returned by mice; verbose = 2 prints all output, including the messages returned by mice. Warnings are always printed, regardless of the value assigned to verbose. Defaults to verbose = 2.
doImputation	A logical switch indicating whether the data should be imputed before extracting the principal component scores. Set to FALSE if the data element in pcAuxData has no missing values (e.g., the imputation was done elsewhere). Defaults to doImputation = TRUE.
castData	A logical switch indicating whether the data element in pcAuxDatashould have its variables re-typed. Keep as FALSE unless the data have been manipulated after running prepData. Defaults to castData = FALSE.
control	An optional list of control parameters (see ’Details’).
micemethods	A list of mice methods to use for imputation.
...	Currently unused

Value

An Reference Class object of class PcAuxData with fields for each of the createPcAux function’s arguments (except for the raw data which are removed to save resources).

dsquire/PcAux documentation built on May 2, 2024, 4:48 a.m.