Andreas - 2 months ago 17

R Question

I am having trouble with formulas, environments, and

`survfit()`

Things work fine for

`lm()`

`survfit()`

I am fitting a series of formulas to some data. So, I call the

modeling function with the formula passed as a variable. Later,

I want to work with the formula from the fitted object.

(From my naive point of view, the trouble comes from survfit not

recording the environment.)

Expected behaviour as seen in

`lm()`

`library("plyr")`

preds <- c("wt", "qsec")

f <- function() {

lm(mpg ~ wt, data = mtcars)

}

fits <- alply(preds, 1, function(pred)

{

modform <- reformulate(pred, response = "mpg")

lm(modform, data = mtcars)

})

fits[[1]]$call$formula

##modform

formula(fits[[1]])

## mpg ~ wt

## <environment: 0x1419d1a0>

Even though

`fits[[1]]$call$formula`

`modform`

still get the original formula with

`formula(fits[[1]])`

But things fail for

`survfit()`

`library("plyr")`

library("survival")

preds <- c("resid.ds", "rx", "ecog.ps")

fits <-

alply(preds, 1, function(pred)

{

modform <- paste("Surv(futime, fustat)", pred, sep = " ~ ")

modform <- as.formula(modform)

print(modform)

fit <- survfit(modform, data = ovarian)

})

fits[[1]]$call$formula

## modform

formula(fits[[1]])

## Error in eval(expr, envir, enclos) : object 'modform' not found

Here (and in contrast to lm-fits),

`formula(fits[[1]])`

work!

So, my specific question is: How can I get back the formula used

to fit

`fits[[1]]`

Answer

The issue is that when `x$formula`

is `NULL`

, for an `lm`

object there is a backup plan to get the formula; this doesn't exist for `survfit`

objects

```
library("plyr")
library("survival")
preds <- c("wt", "qsec")
f <- function() lm(mpg ~ wt, data = mtcars)
fits <- alply(preds, 1, function(pred) {
modform <- reformulate(pred, response = "mpg")
lm(modform, data = mtcars)
})
fits[[1]]$formula
# NULL
```

The formula can be extracted with `formula(fits[[1]])`

which uses the `formula`

generic. The `lm`

S3 method for `formula`

is

```
stats:::formula.lm
# function (x, ...)
# {
# form <- x$formula
# if (!is.null(form)) {
# form <- formula(x$terms)
# environment(form) <- environment(x$formula)
# form
# }
# else formula(x$terms)
# }
```

So when `fits[[1]]$formula`

returns `NULL`

, `forumla.lm`

looks for a `terms`

attribute in the object and finds the formula that way

```
fits[[1]]$terms
```

The `survfit`

objects don't have `x$formula`

or `x$terms`

, so `formula(x)`

givens an error

```
preds <- c("resid.ds", "rx", "ecog.ps")
fits <- alply(preds, 1, function(pred) {
modform <- paste("Surv(futime, fustat)", pred, sep = " ~ ")
modform <- as.formula(modform)
fit <- survfit(modform, data = ovarian)
})
fits[[1]]$formula
# NULL
formula(fits[[1]]) ## error
formula(fits[[1]]$terms)
# list()
```

You can fix this by inserting the formula into the call and evaluating it

```
modform <- as.formula(paste("Surv(futime, fustat)", 'rx', sep = " ~ "))
substitute(survfit(modform, data = ovarian), list(modform = modform))
# survfit(Surv(futime, fustat) ~ rx, data = ovarian)
eval(substitute(survfit(modform, data = ovarian), list(modform = modform)))
# Surv(futime, fustat) ~ rx
# Call: survfit(formula = Surv(futime, fustat) ~ rx, data = ovarian)
#
# n events median 0.95LCL 0.95UCL
# rx=1 13 7 638 268 NA
# rx=2 13 5 NA 475 NA
```

Or by manually putting the formula into `x$call$formula`

```
fit <- survfit(modform, data = ovarian)
fit$call$formula
# modform
fit$call$formula <- modform
fit$call$formula
# Surv(futime, fustat) ~ rx
fit
# Call: survfit(formula = Surv(futime, fustat) ~ rx, data = ovarian)
#
# n events median 0.95LCL 0.95UCL
# rx=1 13 7 638 268 NA
# rx=2 13 5 NA 475 NA
```