Is there any way to calculate the Margin Of Error (MOE) for age and sex population estimates for various ethnicities for custom tables abtained from MDAT site (link attached) :
(( https://data.census.gov/mdat/#/search?ds=ACSPUMS1Y2018&vv=AGEP%2835%3A99%29&cv=SEX&rv=RAC3P%28003,004,005,006,007,008,009%29,AGEP_RC1&wt=PWGTP&AGEP_RC1=%7B%22S%22%3A%22Age%20recode%22,%22R%22%3A%22AGEP%22,%22W%22%3A%22PWGTP%22,%22V%22%3A%5B%5B%2235%3A44%22,%22Between%2035%20and%2044%22%5D,%5B%2245%3A54%22,%22Between%2045%20and%2054%22%5D,%5B%2255%3A64%22,%22Between%2055%20and%2064%22%5D,%5B%2265%3A74%22,%22Between%2065%20and%2074%22%5D,%5B%2275%3A84%22,%22Between%2075%20and%2084%22%5D,%5B%2285%3A99%22,%22Between%2085%20and%2099%22%5D%5D%7D ))
Being an early phase research enthusiast, the method of calculating MOE as explained in the ACS webinar ( MOE 2020 Webinar ) pertaining to the same seems a bit complex for me, as it would require me to access VRE tables.
Did you get an answer yet? Age and sex and race are controlled by estimates IIRC so there’s no margin of error unless you’re getting into more detail than the published age-race-Hispanic-sex estimates