recode: how to avoid nested ifelse

table(factor(x, levels = c("000", "100", "110", "111"), labels = c("none", "es","hs", "cg")))

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]]

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 <pauljohn32 at 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]]

-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com

system.time(replicate(1000, f1(cg, hs, es)))

system.time(replicate(1000, f2(cg, hs, es)))

system.time(replicate(1000, f3(cg, hs, es)))

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 <pauljohn32 at 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]]

--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com

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 <nfultz at 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 <pauljohn32 at 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]]

--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com

-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://joshuawiley.com/
Senior Analyst - Elkhart Group Ltd.
http://elkhartgroup.com