Quantile estimates for subpopulations where some subpopulations only have one case using srvyr and survey R packages - r

Question

I am trying to produce estimates of the 25th percentile of a continuous variable for a series of sub-groups, where the data is taken from a survey that uses sampling weights. I am doing this in R using the survey and srvyr packages.
This issue I face is that in a small minority of cases a sub-group only has one observation and therefore a 25th percentile is meaningless. This would be fine however it results in a error which prevents the percentiles being calculated for those subgroups with sufficient observations.
Error in approxfun(cum.w, xx[oo], method = method, f = f, yleft = min(xx), :
need at least two non-NA values to interpolate
The code runs when the offending groups are removed, however I have had to identify them manually which is far from ideal.
Is there a way to achieve the same outcome but where for single observation groups an NA, or just the value of that observation, is outputted rather than an error? Alternatively is there a neat way of automatically excluding such groups from the calculation?
Below is a reproducible example to illustrate my issue using the apistrat dataset from the survey package.
library(dplyr)
library(survey)
library(srvyr)
data(api)
#25th percentile of api00 by school type and whether school is year round or not
apistrat %>%
as_survey(strata = stype, weights = pw) %>%
group_by(yr.rnd, stype, .drop=TRUE) %>%
summarise(survey_quantile(api00, 0.25, na.rm=T))
#Error in approxfun(cum.w, xx[oo], method = method, f = f, yleft = min(xx), :
#need at least two non-NA values to interpolate
apistrat %>% group_by(yr.rnd, stype) %>% tally() %>% filter(n==1)
#one group out of 6 has only a single api00 observation and therefore a quantile can't be interpolated
#Removing that one group means the code can now run as intended
apistrat %>%
as_survey(strata = stype, weights = pw) %>%
filter(!(yr.rnd=="Yes"&stype=="H")) %>%
group_by(yr.rnd, stype, .drop=TRUE) %>%
summarise(survey_quantile(api00, 0.25, na.rm=T))
#Get the same error if you do it the 'survey' package way
dstrat <- svydesign(id=~1,strata=~stype,data=apistrat, fpc=~fpc)
svyby(~api99, ~stype+yr.rnd, dstrat, svyquantile, quantiles=0.25)

Answer 1

One work-around is to wrap the call to svyquantile() using tryCatch()
> svyq<-function( ...){tryCatch(svyquantile(...), error=function(e) matrix(NA,1,1))}
> svyby(~api99, ~stype+yr.rnd, dstrat, svyq, quantiles=0.25,keep.var=FALSE,na.rm=TRUE)
stype yr.rnd statistic
E.No E No 560.50
H.No H No 532.75
M.No M No 509.00
E.Yes E Yes 456.00
H.Yes H Yes NA
M.Yes M Yes 436.00
With quantiles and svyby you need to be explicit about whether you want standard errors -- the code above doesn't. If you want standard errors, you'd need the error= branch of tryCatch to return an actual svyquantile object with NAs in it.