I did explore tryCatch but wasn't successful. However, I did just try your solution, William, and it worked!

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I just had to modify this line in my function: p <- ((svyciprop(~grp, grp1, family=quasibinomial))[1]) to p <- withWarnings((svyciprop(~grp, grp1, family=quasibinomial))[1]) Then I could use p[1] to get my estimated proportion. Then I used: ind <- length(attr(p, "warnings")) print(ind) if (ind > 0) {msg <- names(warnings()) } else { msg <- "No warnings" } overall[1,5] <- msg to complete my table. Thanks, again, William! Jen On Tue, Mar 6, 2018, 5:57 PM William Dunlap <wdun...@tibco.com> wrote: > tryCatch() is good for catching errors but not so good for warnings, as > it does not let you resume evaluating the expression that emitted > the warning. withCallingHandlers(), with its companion invokeRestart(), > lets you collect the warnings while letting the evaluation run to > completion. > > Bill Dunlap > TIBCO Software > wdunlap tibco.com > > On Tue, Mar 6, 2018 at 2:45 PM, Bert Gunter <bgunter.4...@gmail.com> > wrote: > >> 1. I did not attempt to sort through your voluminous code. But I suspect >> you are trying to reinvent wheels. >> >> 2. I don't understand this: >> >> "I've failed to find a solution after much searching of various R related >> forums." >> >> A web search on "error handling in R" **immediately** brought up >> ?tryCatch, >> which I think is what you want. >> If not, you should probably explain why it isn't, so that someone with >> more >> patience than I can muster will sort through your code to help. >> >> Cheers, >> Bert >> >> >> >> >> >> Bert Gunter >> >> "The trouble with having an open mind is that people keep coming along and >> sticking things into it." >> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) >> >> On Tue, Mar 6, 2018 at 2:26 PM, Jen <plessthanpointohf...@gmail.com> >> wrote: >> >> > 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 >> > >> > [[alternative HTML version deleted]] >> > >> > ______________________________________________ >> > R-help@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. >> > >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@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. >> > > [[alternative HTML version deleted]] ______________________________________________ R-help@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.