standardizeCoefficients: Standardized coefficients

In sfeuerriegel/ResearchGroupTools: Collection of Custom Helper Functions

Description

Computes standardized coefficient for a regression or time series. Three scores are returned:

• "Coef:" This returns the original coefficient β.

• "SdChange" A one standard deviation in the independent variable is linked to percentage increase in the dependent variable. Hence, it is β var(β).

• "StdCoef:" Returns the standardized coefficent. It is calculated through β var(β) / var(y) where y is independent variable.

Usage

standardizeCoefficients(model, hide = NULL)

## S3 method for class 'lm'
standardizeCoefficients(model, hide = NULL)

## S3 method for class 'rq'
standardizeCoefficients(model, hide = NULL)

## S3 method for class 'varest'
standardizeCoefficients(model, hide = NULL)

## S3 method for class 'svarest'
standardizeCoefficients(model, hide = NULL)

Arguments

model	Model. Supported types are linear models (lm), quantile regressions (rq from the quantreg package) or time series (varest or svarest from the vars package).
hide	A string. All variables starting with that name are excluded.

Value

Coefficients (with transformations) for model variables. In case of multivariate models, it returns a list with an element for each dependent variable.

Examples

library(dplyr)
library(vars)
data(Canada)

prod <- differences(as.numeric(Canada[, 2]))
production <- data.frame(Prod = prod, Lag1 = dplyr::lag(prod), Lag2 = dplyr::lag(prod, 2))

m <- lm(Prod ~ Lag1, data = production)
standardizeCoefficients(m)

m <- lm(Prod ~ Lag1 + Lag2, data = production)
standardizeCoefficients(m)

var.2c <- VAR(Canada, p = 2, type = "none")
standardizeCoefficients(var.2c$varresult$e)
std <- standardizeCoefficients(var.2c)
std$e

library(quantreg)
data(stackloss)

qr <- rq(stack.loss ~ stack.x, 0.25)
standardizeCoefficients(qr)

sfeuerriegel/ResearchGroupTools documentation built on May 29, 2019, 8:01 p.m.