RCPA3 (version 1.3.1)

transformC: Returns new variables by transforming existing dataset variables (e.g. dummy variables, standardized variables, rank orders)

Description

Given a variable x, the transformC function generates and returns a tranformed version of x. For example, transformC can take a variable x and return standardized x, or the log of x.

Usage

transformC(type, x, data, response, cutpoints, groups, confirm = TRUE, ...)

Value

A transformed version of x variable, a vector with the same length as x, unless type="dummy.set" in which case transformC returns a data.frame.

Arguments

type

The type of transformation to be made to x. Options include:

• "center"

• "cut" use cutpoints or groups arguments to control cuts

• "dummy" use response argument to identify values of x which should be coded 1 (all other non-missing responses will be coded 0)

• "dummy.set"

• "ln"

• "log10"

• "percent.rank"

• "rank"

• "whole"

• "z"

x

The variable to be transformed, a variable that already exists, should be in dataset$var form unless dataset specified in optional data argument.

data

(Optional) Name of dataset that contains x variable.

response

(Optional) For type="dummy", response is the value or vector of values to be coded 1.

cutpoints

(Optional) For type="cut", a vector of values to serve as lower bounds of ranked categories for transformed x variable.

groups

(Optional) For type="cut", the number of (approximately) same sized groups to create based on x values.

confirm

(Optional) By default, transformC will ask you to confirm you want transformed variable returned (to prevent data loss). Set confirm=FALSE to bypass this check.

...

(Optional) Additional arguments pass to cut2 (for type="cut").

RCPA3 Package Tutorial Videos

• Transforming Variables with RCPA3 Package's transformC Function 22:40

• Complete Playlist of RCPA3 Package Tutorial Videos, includes video for this function and many more.

Textbook References

• Philip H. Pollock and Barry C. Edwards, An R Companion to Political Analysis, 3rd Edition (Thousand Oaks, CA: Sage Publications, Forthcoming 2022), Chapter 3.

• Philip H. Pollock and Barry C. Edwards, The Essentials of Political Analysis, 6th Edition (Thousand Oaks, CA: Sage Publications, 2020), pp. 55-64. ISBN-13: 978-1506379616; ISBN-10: 150637961.

Online Resources

• R Tutorials & Resources for Creating and Transforming Variables, Compiled by Barry C. Edwards

• Sage Edge Resources for Political Analysis Series, for streaming videos, flashcards, and more student resources for textbooks by Pollock and Edwards, from Sage Publications.

• Political Science Data Web Site: Find datasets for your own research and resources to help with the analysis.

Examples

  library(RCPA3)
  
  # don't use confirm=FALSE until you've tested the function call
  transformC("percent.rank", nes$ft.dem, confirm=FALSE)
  transformC("rank", nes$ft.dem, confirm=FALSE)
  transformC("whole", runif(min=0,max=100,n=20), confirm=FALSE)