R help - Dec 2015 - Passing variable names in quotes to a function

I am trying to build a function that can accept variables for a regression.  It
would work something like this:

---
# Y = my response variable (e.g. income)
# X = my key predictor variable (e.g. education)
# subY = a subsetting variable for Y (e.g. race)
# subY.val = the value of the subsetting value that I want (e.g. ?black?)

foo <- function(Y, X, subY, subY.val, dataset){
  
  if(is.na(subY) == F) {
     Y <- paste(Y, ?[?, subY, ?==?, subY.val, ?]?)
  }
  FORMULA <- paste(Y ~ X)
  fit <- some.regression.tool(FORMULA, data=dataset)

  return(some.data.after.processing)
}
---

If I call this function with, foo(income, education, race, ?black?, my.dataset),
I do not get the result that I need because the FORMULA is
"income[race==black] ~ education? when what I need is
?income[race==?black?] ~ education?.  How do I get the quotes to stay on
?black??  Or, is there a better way?

Help appreciated.

--
Brant
	[[alternative HTML version deleted]]

On 02.12.2015 06:11, Brant Inman wrote:
> I am trying to build a function that can accept variables for a regression.
It would work something like this:
>
> ---
> # Y = my response variable (e.g. income)
> # X = my key predictor variable (e.g. education)
> # subY = a subsetting variable for Y (e.g. race)
> # subY.val = the value of the subsetting value that I want (e.g. ?black?)
>
> foo <- function(Y, X, subY, subY.val, dataset){
>
>    if(is.na(subY) == F) {

Not sure why this all is needed, but you can insert here:

if(is.character(subY.val) || is.factor(subY.val)) subY.val <- 
shQuote(subY.val)

Best,
Uwe Ligges

>       Y <- paste(Y, ?[?, subY, ?==?, subY.val, ?]?)
>    }
>    FORMULA <- paste(Y ~ X)
>    fit <- some.regression.tool(FORMULA, data=dataset)
>
>    return(some.data.after.processing)
> }
> ---
>
> If I call this function with, foo(income, education, race, ?black?,
my.dataset), I do not get the result that I need because the FORMULA is
"income[race==black] ~ education? when what I need is
?income[race==?black?] ~ education?.  How do I get the quotes to stay on
?black??  Or, is there a better way?
>
> Help appreciated.
>
> --
> Brant
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
>

Your example and explanation are not complete, but I have the gut feeling that
you could do all this both more efficiently *and* more R-ish.

First of all, why would you pass Y and X separately, to ultimately build the Y ~
X formula within the body of your function?

Secondly, it seems to me that subY and subY.val does something very similar to
the subset argument in, say, lm().

Personally, I would write it like this:

foo <- function(formula, data, subset) {
  if (!missing(subset))
    data <- data[subset, ]
  fit <- some_regression_tool(formula, data = data)

  ## <more code>

  data_after_processing
}
 
with subset = subY == subY.val.

Best,

Philippe
> On 02 Dec 2015, at 06:11, Brant Inman <brant.inman at me.com> wrote:
> 
> I am trying to build a function that can accept variables for a regression.
It would work something like this:
> 
> ---
> # Y = my response variable (e.g. income)
> # X = my key predictor variable (e.g. education)
> # subY = a subsetting variable for Y (e.g. race)
> # subY.val = the value of the subsetting value that I want (e.g. ?black?)
> 
> foo <- function(Y, X, subY, subY.val, dataset){
> 
>  if(is.na(subY) == F) {
>     Y <- paste(Y, ?[?, subY, ?==?, subY.val, ?]?)
>  }
>  FORMULA <- paste(Y ~ X)
>  fit <- some.regression.tool(FORMULA, data=dataset)
> 
>  return(some.data.after.processing)
> }
> ---
> 
> If I call this function with, foo(income, education, race, ?black?,
my.dataset), I do not get the result that I need because the FORMULA is
"income[race==black] ~ education? when what I need is
?income[race==?black?] ~ education?.  How do I get the quotes to stay on
?black??  Or, is there a better way?
> 
> Help appreciated.
> 
> --
> Brant
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.

Thank you for your response.  Here is the problem that I find with your code
(which I had tried).  When you pass a value to the subset argument of the
function, it will not hold the quotes on the subsetting variable?s value.

For example, if I want the function to do  Y[Z==?skinny?] so that we use only
those values of Y where Z is equal to skinny, I need to be able to retain the
quotes around skinny. If you try passing ?Z==?skinny?? to the  function, it will
remove the quotes and give you Z==skinny, which does not work in the subsetting
code.



> On Dec 2, 2015, at 7:10 AM, phgrosjean at sciviews.org wrote:
> 
> Your example and explanation are not complete, but I have the gut feeling
that you could do all this both more efficiently *and* more R-ish.
> 
> First of all, why would you pass Y and X separately, to ultimately build
the Y ~ X formula within the body of your function?
> 
> Secondly, it seems to me that subY and subY.val does something very similar
to the subset argument in, say, lm().
> 
> Personally, I would write it like this:
> 
> foo <- function(formula, data, subset) {
>  if (!missing(subset))
>    data <- data[subset, ]
>  fit <- some_regression_tool(formula, data = data)
> 
>  ## <more code>
> 
>  data_after_processing
> }
> 
> with subset = subY == subY.val.
> 
> Best,
> 
> Philippe
> 
>> On 02 Dec 2015, at 06:11, Brant Inman <brant.inman at me.com>
wrote:
>> 
>> I am trying to build a function that can accept variables for a
regression.  It would work something like this:
>> 
>> ---
>> # Y = my response variable (e.g. income)
>> # X = my key predictor variable (e.g. education)
>> # subY = a subsetting variable for Y (e.g. race)
>> # subY.val = the value of the subsetting value that I want (e.g.
?black?)
>> 
>> foo <- function(Y, X, subY, subY.val, dataset){
>> 
>> if(is.na(subY) == F) {
>>    Y <- paste(Y, ?[?, subY, ?==?, subY.val, ?]?)
>> }
>> FORMULA <- paste(Y ~ X)
>> fit <- some.regression.tool(FORMULA, data=dataset)
>> 
>> return(some.data.after.processing)
>> }
>> ---
>> 
>> If I call this function with, foo(income, education, race, ?black?,
my.dataset), I do not get the result that I need because the FORMULA is
"income[race==black] ~ education? when what I need is
?income[race==?black?] ~ education?.  How do I get the quotes to stay on
?black??  Or, is there a better way?
>> 
>> Help appreciated.
>> 
>> --
>> Brant
>> 	[[alternative HTML version deleted]]
>> 
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> 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.
>