anova - Centering Variables in R -

do centered variables have stay in matrix form when using them in regression equation?

i have centered few variables using scale function center=t , scale=f. converted variables numeric variable, can manipulate data frame other purposes. however, when run anova, different f values, variable, else same.

edit:

what's difference between these two:

scale(df$a, center=true, scale=false)   

which embed matrix within data.frame

and

scale(df$a, center=true, scale=false) df$a = as.numeric(df$a) 

which makes variable numeric, , removes matrix notation within variable?

example of trying do, example doesn't cause problem having:

library(car) library(mass) mtcars$wt_c <- scale(mtcars$wt, center=true, scale=false) mtcars$gear <- as.factor(mtcars$gear) mtcars1     <- as.data.frame(mtcars) # part 1 rlm.mpg   <- rlm(mpg~wt_c+gear+wt_c*gear, data=mtcars1) anova.mpg <- anova(rlm.mpg, type="iii") # part 2 # make wt_c numeric mtcars1$wt_c <- as.numeric(mtcars1$wt_c) rlm.mpg2     <- rlm(mpg~wt_c+gear+wt_c*gear, mtcars1) anova.mpg2   <- anova(rlm.mpg2, type="iii") 

i'll attempt answer both of questions

1. do centered variables have stay in matrix form when using them in regression equation?

i'm not sure mean this, can strip center , scale attributes scale() if referring to. can see in example below same answer whether in 'matrix form' or not.

2. what's difference between these two:

scale(a, center=true, scale=false)   

which embed matrix within data.frame

and

 scale(df$a, center=true, scale=false)  df$a = as.numeric(df$a) 

from file scale() see returns,

"for scale.default, centered, scaled matrix."

you getting matrix attributes scaled , center. as.numeric(aa) strips off attributes difference between first , second method. c(aa) same thing. guess as.numeric() either calls c() (through as.double()) or uses same method does.

 set.seed(1234)   test <- data.frame(matrix(runif(10*5),10,5))   head(test)          x1        x2         x3        x4        x5 1 0.1137034 0.6935913 0.31661245 0.4560915 0.5533336 2 0.6222994 0.5449748 0.30269337 0.2651867 0.6464061 3 0.6092747 0.2827336 0.15904600 0.3046722 0.3118243 4 0.6233794 0.9234335 0.03999592 0.5073069 0.6218192 5 0.8609154 0.2923158 0.21879954 0.1810962 0.3297702 6 0.6403106 0.8372956 0.81059855 0.7596706 0.5019975   # center , scale  testvar <- scale(test[,1])   testvar              [,1]  [1,] -1.36612292  [2,]  0.48410899  [3,]  0.43672627  [4,]  0.48803808  [5,]  1.35217501  [6,]  0.54963231  [7,] -1.74522210  [8,] -0.93376661  [9,]  0.64339300 [10,]  0.09103797 attr(,"scaled:center") [1] 0.4892264 attr(,"scaled:scale") [1] 0.2748823   # put testvar friends  bindvar <- cbind(testvar,test[,2:5])   # run regression 'matrix form' y var  testlm1 <- lm(testvar~.,data=bindvar)   # strip non-name attributes  testvar <- as.numeric(testvar)   # rebind , regress  bindvar <- cbind(testvar,test[,2:5])   testlm2 <- lm(testvar~.,data=bindvar)   # check equality  all.equal(testlm1, testlm2) [1] true 

lm() seems return same thing appears both same.