ACS Data Users Group

Hello, I'm trying to figure out how to calculate margins of error on counts in R. So far I've had no luck. I'm hoping that there's an R package out there that will make this a bit easier, but I've not seen anything as yet.

At the moment I'm working with 5-Yr PUMS data, and have extracted "Artists" (using Occupation codes), for the Massachusetts, Greater Boston and Boston geographies. I've further broken those up by race (white artists X, Black artists Y and so on). Especially with PUMS data I expect there to be some error here, but I've not been able to figure out how to calculate it through R. If anyone had any good pointers/code to share, I'm all ears.

Thanks,

Peter

Hi -

I learned how to do this recently myself. You can use R packages srvyr or survey to use replicate weights to show uncertainty (as used in the PUMS files, these are all the variables with PWGTP[#] in the person file). Here is an example using srvyr:

library(srvyr)
library(tidyverse)

personsRaw <- read.csv("ACS_PUMS_Person_File.csv")

persons_svy <- personsRaw %>% as_survey_rep(
weight = PWGTP,
repweights = matches("PWGTP[0-9]+") ,
scale = 4 / 80,
rscales = rep(1 , 80),
mse = TRUE,
type = "JK1",
variables = c(RAC1P,OCCP)
)

persons_svy %>%
# update the next line to include all desired occupation codes
filter(OCCP >=2600 & OCCP < 2800) %>%
group_by(RAC1P) %>%
# vartype: Report variability as one or more of: standard error ("se", default), confidence interval ("ci"), variance ("var") or coefficient of variation ("cv").
summarize(Employees = survey_total(vartype="ci"))

Note that `library(srvyr)` is a tidyverse wrapper for `library(survey)`. If the rest of your workflow is in base R, you can obtain the results with that basic syntax.

Great yeah, I've looked those up a bit more as well.