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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
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New Methods of Census Record Linking.

Ron Goeken1, Lap Huynh, Thomas Lenius

  • 1Minnesota Population Center.

Historical Methods
|May 14, 2011
PubMed
Summary
This summary is machine-generated.

Researchers can now access linked census data from the Minnesota Population Center (MPC) through its NAPP and IPUMS projects. The MPC developed advanced record-linking techniques, including name similarity scores and machine learning, for creating these valuable linked datasets.

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Area of Science:

  • Demography
  • Data Science
  • Social Sciences

Background:

  • Researchers previously used various record-linking software before the Minnesota Population Center (MPC) released complete count census microdata.
  • Accessibility of linked datasets is crucial for demographic research.

Purpose of the Study:

  • To describe the record-linking techniques employed by the Minnesota Population Center (MPC).
  • To compare the MPC's linking methods with those used by other researchers.
  • To explain modifications for final linked datasets and the role of weighting variables.

Main Methods:

  • The MPC's linking program utilizes cumulative name similarity scores derived from approximately 2.5 billion record comparisons.
  • Support vector machines are employed for classifying potential links within the datasets.
  • The study details modifications made to the final linked datasets.

Main Results:

  • The MPC's record-linking method, featuring name similarity scores and machine learning, enhances the accessibility of linked census microdata.
  • Comparison with other methods highlights the robustness of the MPC's approach.
  • The article clarifies the application of weighting variables in linked data analysis.

Conclusions:

  • The MPC's advanced record-linking techniques provide researchers with readily accessible, high-quality linked datasets.
  • Understanding these methods and the use of weighting variables is essential for leveraging MPC data effectively.
  • The described methodology contributes to the advancement of demographic research through improved data linkage.