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2560 discussions

ACS NonResponse Rate in 2020

by Charles Purvis

I’m still trying to understand what’s going on with the year 2020 American Community Survey (ACS). I went through the Friday, 7/29/21, PDF of the Census Bureau’s powerpoint presentation. https://www.census.gov/newsroom/press-kits/2021/impact-pandemic-2020-acs-1-… <https://www.census.gov/newsroom/press-kits/2021/impact-pandemic-2020-acs-1-…> https://www.census.gov/content/dam/Census/newsroom/press-kits/2021/acs-1-ye… <https://www.census.gov/content/dam/Census/newsroom/press-kits/2021/acs-1-ye…> Census had this to say about “non-response” All surveys typically have some nonresponse bias because those who do not respond tend to be different from those who do respond Our standard methods for mitigating the nonresponse bias are insufficient for this data year The 2020 ACS data collection had the lowest response rate ever for the survey at 71%, down from 86% in 2019 and 92% in 2018 This rate is an average across the entire data collection year Response rates during the peak pandemic months [March-June 2020] were significantly lower The big “wow” is the decline in the “non-response rate” from 86 percent in 2019 to 71 percent in 2020. Of course, my followup question is does this mean that 29 percent of respondents provided “incomplete data” that required their information to be edited / imputed / allocated? Or does it mean that 29 percent of respondents were “totally nonrespondent.” Unfortunately, the 29 percent is “totally nonrespondent”. Here’s the Census Bureau page that shows overall response rates in the ACS from 2005 to 2019, that is, NO useful information (?) from the selected sample. I think. https://www.census.gov/acs/www/methodology/sample-size-and-data-quality/res… <https://www.census.gov/acs/www/methodology/sample-size-and-data-quality/res…> This table is also amazing to show that the “Best” year for the ACS, in terms of response rates, was 2009, at 98.0 percent response rate. These are nonresponse rates for the American Community Survey, not the decennial (the “short form”) Census. # # #

3 years, 4 months

FW: Resources for 2020 ACS Data Release

by Weinberger, Penelope

From: American Community Survey Data Users Group <noreply(a)prb.org> Sent: Friday, July 30, 2021 9:18 AM To: Weinberger, Penelope <pweinberger(a)aashto.org> Subject: Resources for 2020 ACS Data Release [cid:ACS+DUS+logo+from+Test+Site-jpg_2D00_150x0-jpg@prb.org] Update from American Community Survey Data Users Group The Census Bureau announced yesterday that they will not be releasing their standard 2020 ACS 1-year data products in September as planned due to the impact of the pandemic on data quality. Instead, they will be releasing a set of experimental estimates from the 1-year data. They have created several resources to help data users prepare for this change: * A press kit<https://www.census.gov/newsroom/press-kits/2021/impact-pandemic-2020-acs-1-…> includes a PDF version of yesterday's webinar, background materials explaining what experimental data products are, and information about the Census Bureau’s statistical quality standards. A recording of the webinar should be available by late Monday. * A revised 2020 ACS release schedule<https://www.census.gov/programs-surveys/acs/news/data-releases/2020/release…> includes the complete schedule with new planned release dates. * The ACS Resource Hub<https://www.census.gov/programs-surveys/acs/library/flyers/resource-hub.html> flyer and 2020 ACS 1-Year Estimates: What You Need to Know<https://www.census.gov/programs-surveys/acs/library/flyers/flow-chart.html> flyer provide more information. You were sent this email because an administrator sent it to all users in the Everyone role on American Community Survey Data Users Group.

3 years, 4 months

Resources for 2020 ACS Data Release

by Ed Christopher

This may be of interest to some. -------- Forwarded Message -------- Subject: Resources for 2020 ACS Data Release Date: 30 Jul 2021 13:17:45 +0000 From: American Community Survey Data Users Group <noreply(a)prb.org> To: Ed Christopher <edc(a)berwyned.com> [Population Reference Bureau] Update from American Community Survey Data Users Group <https://acsdatacommunity.prb.org/> The Census Bureau announced yesterday that they will not be releasing their standard 2020 ACS 1-year data products in September as planned due to the impact of the pandemic on data quality. Instead, they will be releasing a set of experimental estimates from the 1-year data. They have created several resources to help data users prepare for this change: * A press kit <https://www.census.gov/newsroom/press-kits/2021/impact-pandemic-2020-acs-1-…> includes a PDF version of yesterday's webinar, background materials explaining what experimental data products are, and information about the Census Bureau’s statistical quality standards. A recording of the webinar should be available by late Monday. * A revised 2020 ACS release schedule <https://www.census.gov/programs-surveys/acs/news/data-releases/2020/release…> includes the complete schedule with new planned release dates. * The ACS Resource Hub <https://www.census.gov/programs-surveys/acs/library/flyers/resource-hub.html> flyer and 2020 ACS 1-Year Estimates: What You Need to Know <https://www.census.gov/programs-surveys/acs/library/flyers/flow-chart.html> flyer provide more information. You were sent this email because an administrator sent it to all users in the Everyone role on American Community Survey Data Users Group.

3 years, 4 months

Census Bureau blog post on differential privacy. Warming up with fuzzy data?

by Charles Purvis

Today’s (7/28/2021) blog post by acting Census Bureau director Dr Ron Jarmin is essential reading. And the imbedded youtube videos help us understand what’s going on. Here’s a link to the blog post: https://www.census.gov/newsroom/blogs/director/2021/07/redistricting-data.h… <https://www.census.gov/newsroom/blogs/director/2021/07/redistricting-data.h…> The What is Redistricting video: https://youtu.be/O0MhAue2Tuk <https://youtu.be/O0MhAue2Tuk> The Protecting Privacy video: https://www.youtube.com/watch?v=1AaoaBcHoss <https://www.youtube.com/watch?v=1AaoaBcHoss> Here’s a snippet from the Director’s post: "With these [privacy protecting] parameters, some small areas like census blocks may look “fuzzy,” meaning that the data for a particular block may not seem correct. Importantly, our approach yields high quality data as users combine these "fuzzy” blocks to form more significant geographic units like census tracts, cities, voting districts, counties, and American Indian/Alaska Native tribal areas. Our calibration was designed to achieve acceptable quality thresholds for these levels of geography. So, if you’re looking at block-level data, you may notice situations like the following: Occupancy status doesn’t match population counts. Some blocks may show that the housing units are all occupied, but the population count is zero. Other blocks may show the reverse: the housing units are vacant, but the population count is greater than zero. Children appear to live alone. Some blocks may show a population count for people under age 18 but show no people age 18 and older. Households appear unusually large. For example, you may find blocks with 45 people, but only three housing units. Though unusual, situations like these in the data help confirm that confidentiality is being protected. Noise in the block-level data will require a shift in how some data users typically approach using these census data. Instead of looking for precision in an individual block, we strongly encourage data users to aggregate, or group, blocks together. As blocks are grouped together, the fuzziness disappears. And when you step back with more blocks in view, the details add together and make a sharp picture. " # # # So, as I understand it, it’s not that the Bureau is taking complete microdata records (the household, household members, etc.) and sprinkling them randomly within a census tract, but each individual variable is independently (?) modeled/simulated using their privacy protection parameters. More or less, I guess. If I was a City Planner, the variable that I would/should be most certain of is the count of dwelling units at my city block level. I wouldn’t readily know if those housing units were occupied or vacant, but I could believe with my own eyes(and aerial photography) that a housing unit is present. But if “housing units” are fuzzified (?) using differential privacy, then, meh….. ### Fuzzy Wuzzy was a bear, Fuzzy Wuzzy had no hair, Fuzzy Wuzzy wasn’t fuzzy, was he? ###

3 years, 4 months

Census 2020 PL 94-171 Data: Legacy Format vs API Format

by Charles Purvis

Hello all: The Census 2020 “PL 94-171” file — the “redistricting file” — the “short form” data from the decennial census — will be released by August 16, 2021 in a “legacy format”. This means that it will be released in large data chunks, downloadable from the Census Bureau’s website, but not accessible using the Census API (Application Programming Interface) until (perhaps) September 30, 2021. This means that the PL 94-171 data will not be available (immediately) via data.census.gov <http://data.census.gov/> or r-programs such as TIDYCENSUS. Census Bureau’s main page on Census 2020 PL 94-171: https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-… <https://www.census.gov/programs-surveys/decennial-census/about/rdo/summary-…> Census Bureau’s video on the PL 94-171 data release. Watch It! https://www.youtube.com/watch?v=O0MhAue2Tuk&t=86s <https://www.youtube.com/watch?v=O0MhAue2Tuk&t=86s> But there are two R program packages available to read in the “legacy format” PL 94-171 files: CENSUSAPI https://CRAN.R-project.org/package=censusapi <https://cran.r-project.org/package=censusapi> and PL94171 https://CRAN.R-project.org/package=PL94171 <https://cran.r-project.org/package=PL94171> And they work! I really like PL94171, and will be using it in my analyses between August 16th and to whenever the “API ready” data is available. Attached are my scripts that test the CENSUSAPI, TIDYCENSUS, and PL94171 for the Census 2010 (Rhode Island, California); and the 2018 Test Census (Providence County, RI). # # # And here is the TWITTER stream that alerted me to the presence of the PL94171 package: from the twitterverse: Kyle Walker <https://twitter.com/kyle_e_walker> @kyle_e_walker <https://twitter.com/kyle_e_walker> (July 12, 2021) tidycensus #rstats <https://twitter.com/search?q=%23rstats> users: this means that the soonest we'll have 2020 redistricting data in the package is early October, though you can work with the raw data yourselves in mid-August by downloading from the FTP site. Hansi Lo Wang @hansilowang <https://twitter.com/hansilowang> (July 12, 2021) PRO TIP: If you're confused by the Census Bureau citing two different expected release dates for 2020 census redistricting data — Aug. 16 and Sept. 30 — bureau official Nicholas Jones says in this video: "It's the same data, just in different formats" youtube.com/watch?v=O0MhAu… <https://t.co/C8yYHFsot1> Christopher Kenny @Chris_T_Kenny <https://twitter.com/Chris_T_Kenny> Jul 12 <https://twitter.com/Chris_T_Kenny/status/1414639454548119560> Replying to @kyle_e_walker In that interim, @CoryMcCartan <https://twitter.com/CoryMcCartan/> and I have the PL94171 package on CRAN CRAN.R-project.org/package=PL94171 <https://t.co/nnRbEcRJpc>. It has tools to download, read, and process the PL files once they're available from the FTP. (I look forward to once they're tidycensus readable!) Kyle Walker @kyle_e_walker <https://twitter.com/kyle_e_walker> Jul 12 <https://twitter.com/kyle_e_walker/status/1414648437447053317> Replying to @Chris_T_Kenny @CoryMcCartan excellent, great work! Chuck Purvis @charleypurvis <https://twitter.com/charleypurvis> (July 19, 2021) Replying to @kyle_e_walker The good news is that TIDYCENSUS can currently read the Census 2010 PL 94-171 data. I was sincerely hoping the Census Bureau had the 2020 PL data “API ready” by August 16, but alas, this doesn’t appear to be the case! # # # Hopefully folks can use and improve on my R scripts. I’m still an old-dog-learning-new-tricks with R, so recommendations to improve them would be welcome. And if you’re really ambitious, you can check out the REDIST package (geographic methods for re-districting!). cheers, Chuck Purvis, Hayward, California (formerly of the Metropolitan Transportation Commission, San Francisco, California) # # # Attachments:

3 years, 5 months

FW: *Updated Link and Date* Census Bureau to Host Webinar on Impact of Pandemic on the American Community Survey

by Weinberger, Penelope

From: American Community Survey Data Users Group <noreply(a)prb.org> Sent: Tuesday, July 20, 2021 5:47 PM To: Weinberger, Penelope <pweinberger(a)aashto.org> Subject: *Updated Link and Date* Census Bureau to Host Webinar on Impact of Pandemic on the American Community Survey [cid:ACS+DUS+logo+from+Test+Site-jpg_2D00_150x0-jpg@prb.org] Update from American Community Survey Data Users Group *Updated Link and Date* Census Bureau to Host Webinar on Impact of Pandemic on the American Community Survey The U.S. Census Bureau has scheduled a webinar on Thursday, July 29, at 2 p.m. EDT to explain and answer questions related to the impact of the coronavirus pandemic on 2020 ACS statistics and data products. Speakers: Michael C. Cook, Sr., chief, Public Information Office, U.S. Census Bureau Donna M. Daily, chief, American Community Survey Office, U.S. Census Bureau Login information: CENSUS WebEx Enterprise Site<https://uscensus.webex.com/mw3300/mywebex/default.do?nomenu=true&siteurl=us…> Audio conference access information: Toll-free number: 888-566-5775 Participant passcode: 6714070 Please log in 10-15 minutes early, as some setup is required. An updated browser is recommended. Credentialed media will be able to ask questions following the presentation. Learn More<https://www.census.gov/newsroom/press-releases/2021/webinar-impact-pandemic…> You were sent this email because an administrator sent it to all users in the Everyone role on American Community Survey Data Users Group.

3 years, 5 months

Getting Started with the R Package CTPPr

by Charles Purvis

Hello to the CTPP listserv. Thought I would share something I started several months ago. I somehow got distracted - - baseball or beer or squirrels or something! My ex-colleague mentioned a year or so ago the R-package “CTPPr” produced by Westat staff. Thought I would give it a test drive. It works great for its intended use: table specific downloads of Part 1, 2, 3 data for entire states (or multiple states). Ideally I would flesh out these examples, using the census mapping options in R, as well as combining it with other census R-packages such as TIGRIS and TIDYCENSUS. Here’s my “getting started” R script for extracting CTPP 2006/10 and 2012/16 data using the CTPPr package. Cheers, Chuck Purvis, Hayward, California (formerly with the Metropolitan Transportation Commission, San Francisco, California). ############################################################ # CTPPr_GettingStarted_1.r # Getting started with the Westat R Package "CTPPr" # CTPPr is authored by: Anthony Fucci, Alexander Cates # and Marcelo Simas of Westat # Note that there isn't an option to select only certain # tracts, places, TADs, TAZs, WITHIN a state... only the # ENTIRE state! User may prefer to use the Beyond2020 # software for extracting only some parts within a state! # # Examples Developed by Chuck Purvis, Hayward, California # -- March 21-25, 2021 -- ########################################################### # Install CTPPr onto local computer.. Just need to do once! # I'm just not sure about etiquette for updating packages! install.packages('devtools') devtools::install_github('Westat-Transportation/CTPPr') # Activate/load the CTPPr library for this script. library("CTPPr") # optional libraries to load, depending on how I expand the examples! library('dplyr') library("tidyverse") library("magrittr") # Produce a VIEWER table of ALL CTPP Tables # It defaults to the CTPP 2012-16 data. Not sure about 2006-10.... ctpp_tables() # Demonstrate various examples of the download_ctpp function.... # without geography= or state=, the function defaults to US States, # 50 US States + District of Columbia + Puerto Rico! # Package authors strongly recommend using BOTH geography= and # state= or you will crash the AASHTO servers or worse. # The default datset is the 2012-2016 CTPP. # CTPPr can also be used to pull 2006-2010 CTPP data. # But TABLE NUMBERING can be different between the two databases, # so be really careful! # Note that a simple one-cell table will retrieve three variables: # 1. Geography Variable Name (RESIDENCE, WORKPLACE, or both!) # 2. Estimate # 3. Standard Error (the Authors have divided the MOE by 1.645 to yield SE) # Table A101100 is Total Population! A one-cell table! # "A" -- based on the entire ACS microdata # "1" -- residence-based geographies # "01" -- data universe is "total population" # "100" -- This is Table #100. # These three examples pull US States. totalpop_1216 <- download_ctpp(A101100) totalpop_1216a <- download_ctpp(A101100,dataset='2016') totalpop_0610 <- download_ctpp(A101100,dataset='2010') # This example, weirdly, provides County data for California! Califpop_1216 <- download_ctpp(A101100,dataset='2016', geography='State', state="California") # Example: Counties within California Calpop_1216a <- download_ctpp(A101100,dataset='2016', geography='County', state="California") # Example: Places within California CalPlacePop_1216a <- download_ctpp(A101100,dataset='2016', geography='Place', state="California") # Example: All Census Tracts within California with the Tract Name CalTractPop_1216a <- download_ctpp(A101100,dataset='2016', geography='Tract', state="California", output="Name") # Example: Tracts within California, Using the FIPS Code instead of Name CalTractPop_1216b <- download_ctpp(A101100,dataset='2016', geography='Tract', state="California", output = 'FIPS Code') # Example: Tracts within California, Split FIPS Code # probably need some follow-on examples to split the FIPS code # into 3 separate variables: state, county, tract. CalTractPop_1216c <- download_ctpp(A101100,dataset='2016', geography='Tract', state="California", output = 'Split FIPS Code') # Example: PUMAs within California # And then add a new variable, Coefficient of Variation (SE/Estimate) CalPUMAPop_1216 <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'Name') CalPUMAPop_1216$CV = CalPUMAPop_1216$SE / CalPUMAPop_1216$Estimate # Example: PUMAs within California, FIPS Code CalPUMAPop_1216a <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'FIPS Code') # Example: PUMAs within California, FIPS Code and Name!! CalPUMAPop_1216b <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'FIPS and Name') # Example: PUMAs within California, Split FIPS Code CalPUMAPop_1216c <- download_ctpp(A101100,dataset='2016', geography='PUMA', state="California", output = 'Split FIPS Code') # Example: Metropolitan Statistical Areas within California # Note: CTPPr documentation doesn't mention the State>MSA sum level. # but it works... at least for California MSA_Pop_1216a <- download_ctpp(A101100,dataset='2016', geography='MSA', state="California", output = 'Name') # Example: Principal Cities within Each MSA in California. # Note that MSAs may have multiple Principal Cities!!! MSACity_Pop_1216 <- download_ctpp(A101100,dataset='2016', geography='City', state="California", output = 'Name') # for whatever reason, pulling urbanized areas isn't working. UA_Pop_1216 <- download_ctpp(A101100,dataset='2016', geography='UA', # state="California", output = 'Name') # Other residence and workplace geography include: # OUSA (workplace tables only); TAD; and TAZ, and MCD(12 MCD states) # Pull a two way table: Population by Hispanic (3) by Race (5) # This yields 15 records (3*5) for each County # Two Additional columns are included in this particular data frame: # -- "Hispanic Origin 3" # -- "Race of Person 5" Calif_County_Race_Hisp_1216 <- download_ctpp(A101204,dataset = '2016', output = "FIPS Code", geography = 'County', state = "California") # Pull a REALLY big two-way table: Workers by Occupation (25) # by Industry (15)... # This yields 21,750 observations for the 58 county California, # Columns include: RESIDENCE, "Occupation 25", "Industry 15", # Estimate, and SE. Calif_County_Workers_Occ_Ind_1216 <- download_ctpp(A102214,dataset = '2016', output = "FIPS Code", geography = 'County', state = "California") # The following doesn't work, even though it's listed in the view # of available tables. Be careful!! # I don't think "C" tables are really available .... Calif_County_Workers_Occ_Ind_1216aaa <- download_ctpp(A102214C,dataset = '2016', output = "FIPS Code", geography = 'County', state = "California") ################################################################## # Workplace Tables! (Part 2 Tables) # Total Workers at Work by County of Work # Output columns in the data frame are: WORKPLACE, Estimate, and SE # "A" -- data is from the entire ACS microdata, not just the 5% in PUMS # "2" -- these are tabulated at the work-end (or workplace) # "02" -- the data universe is "total workers at work" # "100" -- this is table #100 Calif_COW_TotWorkers <- download_ctpp(A202100,dataset = '2016', output = "Name", geography = 'County', state = "California") ################################################################## # Worker Flow Tables (Part 3 Tables) # Total Worker Flows, County-to-County, Intra-State California # Intra State California is 58 by 58 counties, for 3,364 records! # 58 * 58 = 3364.... lots of records with zero commuters!! # Output columns include: RESIDENCE, WORKPLACE, Estimate, SE Calif_Co2Co_TotWork <- download_ctpp(id="A302100", dataset = '2016', output = "FIPS and Name", geography = 'County->County', state = "California") # Pull County-to-County workers for four Western US States # This yields 15,876 records, but a lot of the records have 0 workers! Calif_Neighbors_Co2Co_TotWork <- download_ctpp(id="A302100", dataset = '2016', output = "FIPS and Name", geography = 'County->County', state = "California,Arizona,Nevada,Oregon") # Perhaps continue the above example to just retain # Intra-state records, and inter-state into/out of California.... # End of Getting Started Part 1.

3 years, 5 months

New Software, RFP coming

by Weinberger, Penelope

Dear CTPP Community, We are in the development stages of an RFP for a Census Transportation Planning Products (CTPP) data delivery update/refresh. The CTPP data is a special tabulation of census data that is transportation centric. Its chief difference from standard census products is a large amount of workplace based data, data at small geography (but still in tabular form) and flow data from home to work. This is aggregate (census) data, not microdata. Manhan Group is working with us to develop the RFP and doing outreach to generate interested recipients. If you are interested, please let Ya Wang ya(a)manhangroup.com<mailto:ya@manhangroup.com> know. More info is below. The project will have three parts: database backend, API, and front-end data portal. We are open to different vendors for different parts and open to any approach which makes sense. If we are using different vendors, the database backend vendor would need to support the vendor for the API or front-end data portal development. The project aims to overhaul the existing data access solution to the CTPP data products. AASHTO is the sponsor of the project and Manhan Group, LLC is the project manager. The existing data access application is linked here: http://data5.ctpp.transportation.org<http://data5.ctpp.transportation.org/>. The backend database is currently stored in MS SQL server. The existing data is also available for download in batch through a ftp site: ftp://data5.ctpp.transportation.org/ in zipped csv file formats. Linked here is the document explaining the data structure for the CTPP 2012 to 2016 data set: https://ctpp.transportation.org/wp-content/uploads/sites/57/2020/09/Data-St… . Data Structure for CTPP 2012-2016 Data Set<https://ctpp.transportation.org/wp-content/uploads/sites/57/2020/09/Data-St…> Data Structure for CTPP 2012-2016 Data Set 1. Source Data from Census The data from Census comes in a form of ZIP files (one per state). Each ZIP file contains a collection of ctpp.transportation.org The new database would store both the existing CTPP data sets and the upcoming ones. Since CTPP users still want the online web map applications, it might be a good idea to store the census geography corresponding to CTPP geography summary level in the database as well. In addition, the design of the database might need to facilitate the longitudinal comparison between different CTPP datasets. AASHTO will provide equivalent tables which identify comparable variables across different data sets. Finally, the database might need to store information related to the utilization of tables or user information once the API and data portal are developed. As to the API, we would prefer the vendor to use the current technology: REST and GraphQL. But we are open to other API technology as well if the vendor can convince us. Besides allowing users to query and filter the data, the API would also allow users to access feature service layer information. The front-end web application will provide a data portal for non-technical users to query, filter and view the data. Right now, we are at the stage of outreaching to potential vendors. Once we have finalized the RFP, we will send you an official invitation to respond to the RFP. In the meantime, feel free to contact us for any additional information, questions or share your ideas about this project. Best, Ya And Penelope Weinberger She/They CTPP Program Manager AASHTO Ctpp.transportation.org ________________________________

3 years, 5 months

Save the Date June 7 - 9, 2022

by Weinberger, Penelope

Save the Date! CTPP is hosting a technical conference in June 2022. You have just one year to prepare to meet, live and in person in Reno, NV. The Census Data for Transportation Planning Technical conference is coming. Mark your calendars, see you there! Penelope Weinberger Transportation Data Program Manager AASHTO https://data.transportation.org

3 years, 7 months

FW: Call for Nominations: Panel to Evaluate the Quality of the 2020 Census

by Weinberger, Penelope

Be heard! From: NASEM Division of Behavioral and Social Sciences and Education <NASEM_DBASSE(a)nas.edu> Sent: Friday, May 7, 2021 10:44 AM To: Weinberger, Penelope <pweinberger(a)aashto.org> Subject: Call for Nominations: Panel to Evaluate the Quality of the 2020 Census Call for Nominations: Panel to Evaluate the Quality of the 2020 Census View this email in your browser<https://mailchi.mp/nas/panel-to-evaluate-the-quality-of-the-2020-census?e=b…> [https://gallery.mailchimp.com/86e1b30d7b026cdd15adc841f/images/0a4ca141-014…] National Surveys and Statistics [CNSTAT Website]<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> CNSTAT Website<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> [Twitter]<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> Twitter<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> [Subscribe to receive Updates]<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> Subscribe to receive Updates<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> [https://mcusercontent.com/86e1b30d7b026cdd15adc841f/images/8f762818-d124-ab…] The National Academies’ Committee on National Statistics (CNSTAT) is seeking nominations for members of an ad hoc consensus study panel to review and evaluate the quality of the 2020 Census. The panel is to prepare a report that includes conclusions about the quality of the data collected in the 2020 Census and makes recommendations for further research by the Census Bureau to evaluate the quality of the 2020 data and to begin planning the 2030 Census. As is well known, the 2020 U.S. Census was conducted amidst an array of daunting challenges, most notably a forced delay in field operations due to the COVID-19 pandemic. This study is intended as a thorough operational and procedural review of the 2020 Census, to both assess the trustworthiness of the 2020 Census data products and to provide solid ground for the testing and experimentation that will lead to the 2030 Census. Accordingly, the study will review Census Bureau process measures and data quality indicators, contrasting the data with alternative estimates (post-enumeration survey, demographic analysis, administrative records) and comparing with the 2010 Census and other historical census benchmarks. In constituting the panel, CNSTAT seeks a full range of perspectives. The panel should include investigators who are steeped in the workings of the decennial census as well as those with fresh viewpoints but little previous experience with the census. Specific areas of expertise sought for the study include but are not limited to: * Survey and census methodology, including management of large-scale survey field operations; * Statistical and data science experience in the federal statistical system and in state, local, tribal, and territorial agencies; * Geography and population demography, including address list building and maintenance, generation of legal/political/service district boundaries, and assessment of special populations; and * Systems engineering, operations research and evaluation, and methods for ensuring privacy and confidentiality. The study is sponsored by the U.S. Census Bureau. It is anticipated that the panel’s work will build from but also at least partially dovetail with other assessments, including the Census Bureau’s own program of experiments and evaluations and the American Statistical Association’s task force on census quality indicators. The panel is to issue an interim report with initial findings and conclusions within 9 months and a final report with recommendations concerning the 2020 Census and planning for the 2030 Census within 24 months. The National Academies are committed to enhancing diversity and inclusion in order to strengthen the quality of our work. Diverse perspectives contribute to finding innovative approaches and solutions to challenging issues. We encourage the nomination of volunteers who reflect the populations we serve and also welcome in particular nominations of candidates from underrepresented racial and ethnic groups, women, and early career professionals. Nominations will receive maximum consideration if submitted by Friday, May 14, 2021. Nomination Form<https://nationalacademies.us8.list-manage.com/track/click?u=86e1b30d7b026cd…> Please feel free to share this solicitation with your colleagues and networks. If you have questions, please feel free to contact Daniel Cork<mailto:dcork@nas.edu?subject=Call%20for%20Nominations%3A%20Panel%20to%20Evaluate%20the%20Quality%20of%20the%202020%20Census>. The Committee on National Statistics was established in 1972 at the National Academies of Sciences, Engineering, and Medicine to improve the statistical methods and information on which public policy decisions are based. The committee carries out studies, workshops, and other activities to foster better measures and fuller understanding of the economy, the environment, public health, crime, education, immigration, poverty, welfare, and other public policy issues. It also evaluates ongoing statistical programs and tracks the statistical policy and coordinating activities of the federal government, serving a unique role at the intersection of statistics and public policy. The committee’s work is supported by a consortium of federal agencies through a National Science Foundation grant, a National Agricultural Statistics Service cooperative agreement, and several individual contracts. Copyright © 2021 National Academy of Sciences, All rights reserved. You are receiving this email because you signed up to receive emails from the Division of Behavioral and Social Sciences and Education of the National Academies of Sciences, Engineering, and Medicine. Our mailing address is: National Academy of Sciences Division of Behavioral and Social Sciences and Education 500 5th Street, NW Washington, DC 20001 Add us to your address book<https://nationalacademies.us8.list-manage.com/vcard?u=86e1b30d7b026cdd15adc…> Want to change how you receive these emails? 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