search for: bctran

...) load("sel.day.txt") sel.p1<-window(sel, start=as.POSIXct("2008-04-05"), end=as.POSIXct("2009-04-01")) pairs(~v.obs+ snow+ HH6.1+ Q.Enz+ pcpt+ qd,data=sel.p1,gap=0.4,cex.labels=1.5) In Sheather: "A Modern Approach to Regression with R" the function bctrans is used to calculate lambda for the variables. I use "yeo.johnson" since there are values=0 in the data. Doing this creates following output: 2> summary(bctrans(~v.obs+ snow+ pcpt+ Q.Enz+ qd+ HH6.1, data=sel.p1, family="yeo.johnson")) yeo.johnson Transformations to Multin...

...form my variables. I wanted to ask what is the preferred way to find out if predictor and/or response needs to be transformed and if yes how (log-transform?). I found a procedure in "A modern approach to Regressoin in R" (Sheather, 2009): There they suggest an approach with the function bctrans from alr3...but it seems that it is deprecated. So what is the best way (box-cox test) find the best transformation for predictor and response simultaneously? AFAIK boxcox from MASS is used only used for transformation of the predictor? Thank you very much Johannes --

...x(t1[,83:115]) denial <- apply(demos[,11:14],c(1,2),as.numeric) # convert to numeric denial.score <- rowMeans(denial) # subject means (no missing data) hb <- apply(demos[,15:22],c(1,2),as.numeric) # convert to numeric num <- demos[,26:30] num <- demos[,c(26:30,7,10,25,33)] # include bctrans,cc..,lc..,pc.. num[num=="a"] <- 1 # recode a-c to numbers to make scoring easier num[num=="b"] <- 2 num[num=="c"] <- 3 num[num=="1/4"] <- .25 # happened 2x in pctrans - really a wrong answer num <- apply(num,c(1,2),as.numeric) num.correct <...