corr.mreg: Multiple Regression Analysis

In adoocavo/Rstat_M1: Basic Statistical Methods in R

Multiple Regression Analysis

Description

Multiple Regression Analysis

Usage

corr.mreg(xd, y, form, xd2, form2, step = 0:4, newd, pvx, xrng, nx,
  alp = 0.05, dig = 4)

Arguments

xd	Data frame of independent variables (explanatory variables)
y	Vector of dependent variable (response variable) data
form	Formula of regression model (ex: y ~ x1 + x2)
xd2	Data frame of independent variables in model2 (step=4, 5)
form2	Formula of regression model2 (ex: y ~ x1 * x2) (step=4, 5)
step	Steps of multiple regression analysis, Default: 0:4
newd	Data frame of independent variables for step 6
pvx	Designated number of independent variables for step 6(step=7)
xrng	Range of independent variables for step 7
nx	Designated number of independent variables for step 7
alp	Level of significance, Default: 0.05
dig	Number of digits below the decimal point, Default: 4

Value

None.

Examples

mpg = mtcars$mpg
xd = mtcars[4:6]
attach(xd)
form = mpg ~ hp + drat + wt
corr.mreg(xd, mpg, form, step=0:3)

form2 = mpg ~ hp * drat + wt
xd2 = data.frame(hp, drat, wt, hpd= hp * drat)
corr.mreg(xd, mpg, form, xd2, form2, step=4:5)

adoocavo/Rstat_M1 documentation built on March 19, 2022, 3:34 a.m.