census-2020-amc-mdf-replicates.yaml

Name: Estimating Confidence Intervals for 2020 Census Statistics Using Approximate Monte Carlo Simulation (2020 Census Production Run)
Description: >-
  The 2020 Census Production Settings Demographic and Housing Characteristics (DHC) Approximate Monte Carlo (AMC) method seed Privacy Protected Microdata File (PPMF0)
  and PPMF replicates (PPMF1, PPMF2, ..., PPMF50) are a set of microdata files intended for use in estimating the magnitude of error(s) introduced by the 2020 
  Census Disclosure Avoidance System (DAS) into the 2020 Census Redistricting Data Summary File (P.L. 94-171), the Demographic and Housing Characteristics File, and the Demographic Profile. 
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  The PPMF0 was the source of the publicly released, official 2020 Census data products referenced above, and was created by executing the 2020 DAS TopDown Algorithm (TDA) using the confidential 
  2020 Census Edited File (CEF) as the initial input; the official location for the PPMF0 is [on the United States Census Bureau FTP server](https://www2.census.gov/programs-surveys/decennial/2020/data/privacy-protected-microdata-file/), but we also include a copy of it here for convenience. The replicates were then created by executing the 2020 DAS TDA repeatedly with the PPMF0 as its initial input. 
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  Inspired by analogy to the use of bootstrap methods in non-private contexts, U.S. Census Bureau (USCB) researchers explored whether simple calculations 
  based on comparing each PPMFi to the PPMF0 could be used to reliably estimate the scale of errors introduced by the 2020 DAS, and generally found this approach 
  worked well.
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  The PPMF0 and PPMFi files contained here are provided so that external researchers can estimate properties of DAS-introduced error without privileged 
  access to internal USCB-curated data sets; further information on the estimation methodology can be found in [Ashmead et. al 2024](https://github.com/uscensusbureau/AMC_Confidence_Intervals/blob/main/Approx_Monte_Carlo_confidence_interval_paper.pdf). 
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  The 2020 DHC AMC seed PPMF0 and PPMF replicates have been cleared for public dissemination by the USCB Disclosure Review Board (CBDRB-FY22-DSEP-004). 
  The PPMF0 and PPMF replicates contain all Person and Units attributes necessary to produce the 2020 Census Redistricting Data Summary File (P.L. 94-171), the Demographic and Housing Characteristics File, and the Demographic Profile for both the United States and 
  Puerto Rico, and include geographic detail down to the Census Block level. They do not include attributes specific to either the Detailed DHC-A or Detailed DHC-B 
  products; in particular, data on Major Race (e.g., White Alone) is included, but data on Detailed Race (e.g., Cambodian) is not included in the PPMF0 and replicates.
Documentation: "[AMC Replicates README (Updated 9/17/2024)](https://uscb-2020-product-releases.s3.amazonaws.com/decennial/amc/2020/mdf/2020-dhc-mdf-replicates/ppmf/README.html)"
Contact: 2020DAS@census.gov
ManagedBy: "[United States Census Bureau](http://www.census.gov/)"
UpdateFrequency: Not Updated
Tags:
  - census
  - decennial census
  - 2020 census
  - differential privacy
  - disclosure avoidance
  - ethnicity
  - group quarters
  - hispanic
  - latino
  - housing
  - housing units
  - noisy measurements
  - population
  - race
  - redistricting
  - demographic and housing characteristics file
  - dhc
  - voting age
  - household type
  - relation-to-householder
  - age
  - single year of age
  - approximate monte carlo
  - approximate monte carlo replicates
  - microdata
License: CC0 1.0 Universal
Resources:
  - Description: 2020 Census Production Settings Demographic and Housing Characteristics Approximate Monte Carlo method seed Privacy Protected Microdata File and PPMF replicates
    ARN: arn:aws:s3:::uscb-2020-product-releases/decennial/amc/2020/mdf/2020-dhc-mdf-replicates
    Region: us-west-2
    Type: S3 Bucket
  - Description: "Census Open Data S3 Inventory"
    ARN: arn:aws:s3:::uscb-opendata-inventory
    Region: us-west-2
    Type: S3 Bucket
DataAtWork:
  Tools & Applications:
    - Title: Estimating Confidence Intervals Using Approximate Monte Carlo Simulation Iterations (Jupyter Notebook)
      URL: https://github.com/uscensusbureau/AMC_Confidence_Intervals/tree/main
      AuthorName: Ashmead, R., Hawes, M. B., Pritts, M., Zhuravlev, P., Keller, S. A.
  Publications:
    - Title: An Approximate Monte Carlo Simulation Method for Estimating Uncertainty and Constructing Confidence Intervals for 2020 Census Statistics
      URL: https://github.com/uscensusbureau/AMC_Confidence_Intervals/blob/main/Approx_Monte_Carlo_confidence_interval_paper.pdf
      AuthorName: Ashmead, R., Hawes, M. B., Pritts, M., Zhuravlev, P., Keller, S. A.