I still argue for na.rm=FALSE, but that is cute, also substantially faster
f1 <- function(x1, x2, x3) do.call(paste0, list(x1, x2, x3))
f2 <- function(x1, x2, x3) pmax(3*x3, 2*x2, es, 0, na.rm=FALSE)
f3 <- function(x1, x2, x3) Reduce(`+`, list(x1, x2, x3))
f4 <- function(x1, x2, x3) rowSums(cbind(x1, x2, x3))
es <- rep(c(0, 0, 1, 0, 1, 0, 1, 1, NA, NA), 1000)
hs <- rep(c(0, 0, 1, 0, 1, 0, 1, 0, 1, NA), 1000)
cg <- rep(c(0, 0, 0, 0, 1, 0, 1, 0, NA, NA), 1000)
system.time(replicate(1000, f1(cg, hs, es)))
system.time(replicate(1000, f2(cg, hs, es)))
system.time(replicate(1000, f3(cg, hs, es)))
system.time(replicate(1000, f4(cg, hs, es)))
> system.time(replicate(1000, f1(cg, hs, es)))
user system elapsed
22.73 0.03 22.76
> system.time(replicate(1000, f2(cg, hs, es)))
user system elapsed
0.92 0.04 0.95
> system.time(replicate(1000, f3(cg, hs, es)))
user system elapsed
0.19 0.02 0.20
> system.time(replicate(1000, f4(cg, hs, es)))
user system elapsed
0.95 0.03 0.98
R version 3.0.0 (2013-04-03)
Platform: x86_64-w64-mingw32/x64 (64-bit)
On Fri, Jun 7, 2013 at 7:25 PM, Neal Fultz <nfu...@gmail.com> wrote:
> I would do this to get the highest non-missing level:
>
> x <- pmax(3*cg, 2*hs, es, 0, na.rm=TRUE)
>
> rock chalk...
>
> -nfultz
>
> On Fri, Jun 07, 2013 at 06:24:50PM -0700, Joshua Wiley wrote:
>> Hi Paul,
>>
>> Unless you have truly offended the data generating oracle*, the
>> pattern: NA, 1, NA, should be a data entry error --- graduating HS
>> implies graduating ES, no? I would argue fringe cases like that
>> should be corrected in the data, not through coding work arounds.
>> Then you can just do:
>>
>> x <- do.call(paste0, list(es, hs, cg))
>>
>> > table(factor(x, levels = c("000", "100", "110", "111"), labels = c("none",
>> > "es","hs", "cg")))
>> none es hs cg
>> 4 1 1 2
>>
>> Cheers,
>>
>> Josh
>>
>> *Drawn from comments by Judea Pearl one lively session.
>>
>>
>> On Fri, Jun 7, 2013 at 6:13 PM, Paul Johnson <pauljoh...@gmail.com> wrote:
>> > In our Summer Stats Institute, I was asked a question that amounts to
>> > reversing the effect of the contrasts function (reconstruct an ordinal
>> > predictor from a set of binary columns). The best I could think of was to
>> > link together several ifelse functions, and I don't think I want to do this
>> > if the example became any more complicated.
>> >
>> > I'm unable to remember a less error prone method :). But I expect you
>> > might.
>> >
>> > Here's my working example code
>> >
>> > ## Paul Johnson <pauljohn at ku.edu>
>> > ## 2013-06-07
>> >
>> > ## We need to create an ordinal factor from these indicators
>> > ## completed elementary school
>> > es <- c(0, 0, 1, 0, 1, 0, 1, 1)
>> > ## completed high school
>> > hs <- c(0, 0, 1, 0, 1, 0, 1, 0)
>> > ## completed college graduate
>> > cg <- c(0, 0, 0, 0, 1, 0, 1, 0)
>> >
>> > ed <- ifelse(cg == 1, 3,
>> > ifelse(hs == 1, 2,
>> > ifelse(es == 1, 1, 0)))
>> >
>> > edf <- factor(ed, levels = 0:3, labels = c("none", "es", "hs", "cg"))
>> > data.frame(es, hs, cg, ed, edf)
>> >
>> > ## Looks OK, but what if there are missings?
>> > es <- c(0, 0, 1, 0, 1, 0, 1, 1, NA, NA)
>> > hs <- c(0, 0, 1, 0, 1, 0, 1, 0, 1, NA)
>> > cg <- c(0, 0, 0, 0, 1, 0, 1, 0, NA, NA)
>> > ed <- ifelse(cg == 1, 3,
>> > ifelse(hs == 1, 2,
>> > ifelse(es == 1, 1, 0)))
>> > cbind(es, hs, cg, ed)
>> >
>> > ## That's bad, ifelse returns NA too frequently.
>> > ## Revise (becoming tedious!)
>> >
>> > ed <- ifelse(!is.na(cg) & cg == 1, 3,
>> > ifelse(!is.na(hs) & hs == 1, 2,
>> > ifelse(!is.na(es) & es == 1, 1,
>> > ifelse(is.na(es), NA, 0))))
>> > cbind(es, hs, cg, ed)
>> >
>> >
>> > ## Does the project director want us to worry about
>> > ## logical inconsistencies, such as es = 0 but cg = 1?
>> > ## I hope not.
>> >
>> > Thanks in advance, I hope you are having a nice summer.
>> >
>> > pj
>> >
>> > --
>> > Paul E. Johnson
>> > Professor, Political Science Assoc. Director
>> > 1541 Lilac Lane, Room 504 Center for Research Methods
>> > University of Kansas University of Kansas
>> > http://pj.freefaculty.org http://quant.ku.edu
>> >
>> > [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
>> > 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.
>>
>>
>>
>> --
>> Joshua Wiley
>> Ph.D. Student, Health Psychology
>> University of California, Los Angeles
>> http://joshuawiley.com/
>> Senior Analyst - Elkhart Group Ltd.
>> http://elkhartgroup.com
>>
>> ______________________________________________
>> 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.
--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com
______________________________________________
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.
