> From a dataframe there are 27 variables of interest, with the
> prefix of "pre".
>
> [7] "Decision" "MHCDate" "pre01" "pre01111" "pre012" "pre013"
> [13] "pre02" "pre02111" "pre02114" "pre0211" "pre0212" "pre029"
> [19] "pre03a" "pre0311" "pre0312" "pre03" "pre04" "pre05"
> [25] "pre06" "pre07" "pre08" "pre09" "pre10" "pre11"
> [31] "pre12" "pre13" "pre14" "pre15" "pre16"
>
> I want to combine these variables into new variables, using the
> following criteria :
>
> (1) create a single variable PRE, when any of the 27 'pre' variables
> have a value >= '1'
> (2) create a variable HOM, when any of the pre01, pre01111, pre012,
> pre013 variables have a value >= '1'
> (3) create a variable ASS, when any of the pre02, pre02111, pre02114,
> pre0211, pre0212, pre029 variables have a value >= '1'
> (4) create a variable SEX, when any of the pre03a, pre0311, pre0312,
> pre03 variables have a value >= '1'
> (5) create a variable VIO, when any of the pre01 to pre06 variables
> have a value >= '1'
> (6) create a variable SERASS. If pre02111 or pre2114 >= '1', assign a
> value of 1, if there is a value of 1 or greater for pre0211 assign a
> value of 2; & if there is a value of
> 1 or greater for pre0212: assign a value of 3; if there is a value
> of 1 or greater for pre2029 assign a value of 4; everything else = 0.
> If a case has multiple values, 02111 prevails over 2114, 2114
> prevails over 0211, 0211 prevails over 0212; 0212 prevails over 2029.
>
>
> I believe I can generate new variables (1) - (5) using code such
> as: ASS <- (reoffend$pre02 | reoffend$pre02111 | reoffend$pre02114 |
> reoffend$pre0211 | reoffend$pre0212 | reoffend$pre029 >= '1')
>
>
> I have three questions:
>
> 1. If this is correct, what is the most efficient way to generate (1)
> without having to type all the variable names. The following does not
> work: PRE <- reoffend [,9:35], >= '1'
Try something like this (data frame simplified):
df <- data.frame(pre1=c(0,1,1,2),
pre2=c(0,0,1,0),
foo=c(0,0,1,3))
precols <- grep("pre", names(df))
gt1 <- function(x) x>=1
PRE <- apply(apply(df[,precols], 2, gt1), 1, any)
> 2. I am unsure as to how to generate Example 6.
SERASS <- rep(0, nrow(df))
SERASS[df$pre2029>=1] <- 4
SERASS[df$pre0212>=1] <- 3
SERASS[df$pre0211>=1] <- 2
SERASS[df$pre02111>=1 | df$pre2114>=1] <- 1
> 3. I wanted to exclude cases with a reoffend$Decision of value of 3,
> using the code below. However, I received a message saying there were
> NAs produced, however, the raw variable did not have NAs.
>
> > MHT.decision <- reoffend[reoffend$Decision >= '2',]
> > table(MHT.decision)
> Error in vector("integer", length) : vector size cannot be NA
> In addition: Warning messages:
> 1: NAs produced by integer overflow in: pd * (as.integer(cat) - 1L)
> 2: NAs produced by integer overflow in: pd * nl
>
> > table(reoffend$Decision)
> 1 2 3
> 1136 445 66
I doubt that you want quotes around the '2' when defining MHT.decision.
Regards,
Richie.
Mathematical Sciences Unit
HSL
------------------------------------------------------------------------
ATTENTION:
This message contains privileged and confidential inform...{{dropped:20}}
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
