typecast: Variables type

In mi: Missing Data Imputation and Model Checking

Description

Function for determinig the variable type.

Usage

  typecast( object )
  ## S4 method for signature 'ANY'
typecast( object )
  ## S4 method for signature 'matrix'
typecast( object )
  ## S4 method for signature 'data.frame'
typecast( object )  
  ## S4 method for signature 'list'
typecast( object )

Arguments

object

Vector, matrix, or data frame of data to determin the type of.

Details

The variable type of a vector, or vector of variable types for each variable in the dataset.

Value

fixed	varaibles that contain only one value.
binary	variables that contain two values.
ordered-categorical	variables that contain 3 to 5 postive values.
unorderd-categorial	variables that contain characters or more than 5 postive levels
positive-continuous	variables that contain more than 5 postive values, NOT including 0s.
nonnegative	variables that contain more than 5 postive values, including 0s.
continuous	variables that are not belong to any of the above types.
log-continuous	log-scaled continuous variable

Author(s)

Yu-Sung Su [e-mail], Masanao Yajima [e-mail], M.Grazia Pittau [e-mail]

References

Yu-Sung Su, Andrew Gelman, Jennifer Hill, Masanao Yajima. (2011). “Multiple Imputation with Diagnostics (mi) in R: Opening Windows into the Black Box”. Journal of Statistical Software 45(2).

See Also

mi

Examples

data(CHAIN)
class(CHAIN)

typecast(CHAIN[,1]) # for vector

typecast(as.matrix(CHAIN))# for matrix

typecast(CHAIN) # for data.frame

mi documentation built on May 2, 2019, 4:43 p.m.