impute: Wrapper for the mice package

In kamclean/finalpsm: Propensity-score matching with tidyverse and finalfit

Wrapper for the mice package

Description

Impute missing at random data using the mice package in a tidyverse approach.

Usage

impute(
  data,
  impute,
  fixed = NULL,
  ignore = NULL,
  quiet = T,
  m = 5,
  maxit = 5,
  meth = "pmm",
  seed = 500,
  ...
)

Arguments

data	Dataframe
impute	Vector of column names containing variables for use in the imputation algorithm and for imputation.
fixed	Optional vector of column names containing variables for use in the imputation algorithm but NOT for imputation.
ignore	Optional vector of column names containing variables NOT for use in the imputation algorithm OR for imputation.
quiet	Logical value to hide the output of the imputation process (default = T)
m	The number of imputations to be performed (default = 5)
maxit	is the number of iterations for each imputation (see mice::mice() function).
seed	random seed parameter which is useful for reproducibility.
...	Additional arguments to be passed to the mice::mice() function.
method	The imputation method to be used for each column in data (see mice::mice() function)

Value

Long dataset containing the original (unimputed) data, with each imputed dataset appended.

kamclean/finalpsm documentation built on Oct. 3, 2023, 3:52 a.m.