[R] Capturing warning within user-defined function

[Jen]

Hi, I am trying to automate the creation of tables for some simply
analyses. There are lots and lots of tables, thus the creation of a
user-defined function to make and output them to excel.

My problem is that some of the analyses have convergence issues, which I
want captured and included in the output so the folks looking at them know
how to view those estimates.

I am successfully able to do this in a straightforward set of steps.
However, once I place those steps inside a function it fails.

Here's the code (sorry this is a long post):

# create data
wt <- rgamma(6065, 0.7057511981,  0.0005502062)
grp <- sample(c(replicate(315, "Group1"), replicate(3672, "Group2"),
replicate(1080, "Group3"), replicate(998, "Group4")))
dta <- data.frame(grp, wt)
head(dta)
str(dta)

# declare design
my.svy <- svydesign(ids=~1, weights=~wt, data=dta)

# subset
grp1 <- subset(my.svy, grp == "Group1")

# set options and clear old warnings
options(warn=0)
assign("last.warning", NULL, envir = baseenv())

## proportions and CIs
p <- ((svyciprop(~grp, grp1, family=quasibinomial))[1])

# save warnings
wrn1 <- warnings(p)

ci_l <- (confint(svyciprop(~grp, grp1, family=quasibinomial), 'ci')[1])
ci_u <- (confint(svyciprop(~grp, grp1, family=quasibinomial), 'ci')[2])

## sample counts
n <- unwtd.count(~grp, grp1)[1]

## combine into table
overall <- data.frame(n, p, ci_l, ci_u)
colnames(overall) <- c("counts", "Group1", "LL", "UL")

## add any warnings
ind <- length(wrn1)
ind

if (ind == 0) { msg <- "No warnings" }
if (ind > 0) {msg <- names(warnings()) }
overall[1,5] <- msg

print(overall)

Here's the output from the above:

> # set options and clear old warnings
> options(warn=0)
> assign("last.warning", NULL, envir = baseenv())
>
> ## proportions and CIs
> p <- ((svyciprop(~grp, grp1, family=quasibinomial))[1])
Warning message:
glm.fit: algorithm did not converge
>
> # save warnings
> wrn1 <- warnings(p)
>
> ci_l <- (confint(svyciprop(~grp, grp1, family=quasibinomial), 'ci')[1])
Warning message:
glm.fit: algorithm did not converge
> ci_u <- (confint(svyciprop(~grp, grp1, family=quasibinomial), 'ci')[2])
Warning message:
glm.fit: algorithm did not converge
>
> ## sample counts
> n <- unwtd.count(~grp, grp1)[1]
>
> ## combine into table
> overall <- data.frame(n, p, ci_l, ci_u)
> colnames(overall) <- c("counts", "Group1", "LL", "UL")
>
> ## add any warnings
> ind <- length(wrn1)
> ind
[1] 1
>
> if (ind == 0) { msg <- "No warnings" }
> if (ind > 0) {msg <- names(warnings()) }
> overall[1,5] <- msg
>
> print(overall)
       counts       Group1           LL           UL
          V5
counts    315 2.364636e-12 2.002372e-12 2.792441e-12 glm.fit: algorithm did
not converge

Here's the function:

est <- function(var) {

## set up formula
formula <- paste ("~", var)

## set options and clear old warning
options(warn=0)
assign("last.warning", NULL, envir = baseenv())

## proportions and CIs
p <- ((svyciprop(as.formula(formula), grp1, family=quasibinomial))[1])

## save warnings
wrn1 <- warnings(p)

ci_l <- (confint(svyciprop(as.formula(formula) , grp1,
family=quasibinomial), 'ci')[1])
ci_u <- (confint(svyciprop(as.formula(formula) , grp1,
family=quasibinomial), 'ci')[2])

## sample counts
n <- unwtd.count(as.formula(formula), grp1)[1]

## combine into table
overall <- data.frame(n, p, ci_l, ci_u)
colnames(overall) <- c("counts", "Group1", "LL", "UL")


## add any warnings
ind <- length(warnings(p))
print(ind)

if (ind == 0) { msg <- "No warnings" }
if (ind > 0) {msg <- names(warnings()) }
overall[1,5] <- msg

print(overall)

}

Here's the output from running the function:

> est("grp")
[1] 0
       counts       Group1           LL           UL          V5
counts    315 2.364636e-12 2.002372e-12 2.792441e-12 No warnings
Warning messages:
1: glm.fit: algorithm did not converge
2: glm.fit: algorithm did not converge
3: glm.fit: algorithm did not converge

So, the warnings are showing up in the output at the end of the function
but they're not being captured like they are when run outside of the
function. Note the 0 output from print(ind) and V7 has "No warnings".
I know a lot of things "behave" differently inside functions. Case in
point, the use of "as.formula(var)" rather than just "~grp" being passed to
the function.

I've failed to find a solution after much searching of various R related
forums. I even posted this to stackoverflow but with no response. So, if
anyone can help, I'd be appreciative.

(sidenote: I used rgamma to create my sampling weights because that's what
most resembles the distribution of my weights and it's close enough to
reproduce the convergence issue. If I used rnorm or even rlnorm or rweibull
I couldn't reproduce it. Just FYI.)

Best,

Jen

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